Fulltime Machine Learning Engineers openings in Boston on September 01, 2022

Staff Machine Learning Engineer at Mozilla

Location: Boston

The Company

Pocket empowers people to discover, organize, consume, and share content that matters to them. Our apps and platform are essential ways that tens of millions of people discover and consume content on the web. Pocket is the Web, curated: for you and by you.

The Opportunity

Build the systems connecting millions of people to the content worthy of their time and attention. We are looking for a Staff Machine Learning engineer to partner with the editorial and product teams to develop the recommendation systems that power Pocket’s discovery surfaces and the Firefox new tab. Machine learning engineers are responsible for designing and evolving both algorithmic and human-in-the-loop recommendation systems. Pocket is committed to recommending high-quality content at scale while respecting our readers’ data and privacy.

We seek applied machine learning experts who can both design algorithms and architectures to satisfy product requirements and also help deploy their solutions in production. Pocket recommendations combine content and engagement signals with the human expertise of our editorial team. Our recommendation systems reflect editorial principles, Mozilla’s values, and the pocket mission. We optimize our systems to enable users to discover content that they can consume on their terms and at their pace.

People who excel on our team thrive in small, dynamic environments. We contribute in many areas beyond machine learning, including product engineering, machine learning operations, and data modeling, among others.

What You’ll Do
• Work closely with Pocket editorial, product management, and experience design teams to deliver high-quality features and solutions
• Be involved in end-to-end development, exploring new applications and techniques within natural language processing, applied machine learning, and explainable and privacy-aware ML
• Enhance our machine learning infrastructure.
• Write robust production-level code and engage in code reviews.
What You Bring
• Technical education in Computer Science, Information Science, Engineering, or equivalent experience (Master’s degree or higher preferred)
• 3+ years of relevant experience in Machine Learning Engineering:
• shipping high-quality machine learning solutions to production
• design and analysis of experiments (A/B tests) to validate iterative system development
• conceptual familiarity with feature stores, monitoring and observability, data distribution shifts
• Flexible and comfortable working within a distributed organization and with minimal process. This role allows for a high degree of ownership and requires rapid iteration.
• Motivation to learn continuously and help define research and development practices in an applied setting
• Excellent verbal and written communication skills and willingness to convey algorithmic or engineering considerations to non-experts.
• Experienced in building recommendation systems on cloud platforms like AWS Sagemaker or Google Cloud ML.
Bonus Experience
• AWS SageMaker, Google Cloud ML
• ML: Scikit-Learn, PyTorch, Hugging Face, Metaflow
• Storage: Snowflake, AWS Feature Groups, AWS S3, AWS DynamoDB
• Orchestrators: Airflow, Prefect
• Data modeling: DBT
Commitment to diversity, equity, inclusion, and belonging

Mozilla understands that valuing diverse creative practices and forms of knowledge are crucial to and enrich the company’s core mission. We encourage applications from everyone, including members of all equity-seeking communities, such as (but certainly not limited to) women, racialized and Indigenous persons, persons with disabilities, persons of all sexual orientations, gender identities and expressions.

We will ensure that qualified individuals with disabilities are provided reasonable accommodations to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment, as appropriate. Please contact us at hiringaccommodation@ to request an accommodation.

We are an equal opportunity employer. We do not discriminate on the basis of race (including hairstyle and texture), religion (including religious grooming and dress practices), gender, gender identity, gender expression, color, national origin, pregnancy, ancestry, domestic partner status, disability, sexual orientation, age, genetic predisposition, medical condition, marital status, citizenship status, military or veteran status, or any other basis covered by applicable laws. Mozilla will not tolerate discrimination or harassment based on any of these characteristics or any other unlawful behavior, conduct, or purpose.

Group: C

R1865
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Machine Learning Engineer at InstaDeep Ltd

Location: Boston

ABOUT INSTADEEP

InstaDeep Ltd is a leading company that develops cutting-edge artificial intelligence products and solutions for major global and local clients in Europe, the US, Africa, and the Middle East. We focus on developing enterprise decision making systems that solve existing problems across a range of industries using advanced machine learning, reinforcement learning, and deep learning. Our expertise spans across research, product and solution development, allowing the whole end-to-end solution to be developed in-house across our teams in London, Paris, Lagos, Tunis, Dubai, and Cape Town.

Our proactive approach to research, combined with a broad spectrum of high-quality clients, ensures a challenging and exciting environment to work and thrive in. In our mission to stay ahead of the curve, we are proud to partner with firms such as Google DeepMind, Nvidia and Intel, and world-class universities such as Oxford, University of Michigan and French Universities.

Our research team publishes advanced research on reinforcement learning in top AI conferences such as NeurIPS and collaborates with world-leading researchers and companies.

From Q2 2022, InstaDeep is expanding in the United States. With this aim, InstaDeep is looking for a Machine Learning Engineer to support the development of its US activities.

JOB DESCRIPTION

In this role at InstaDeep you will report to the Research Lead. You will design and create the algorithms capable of learning and making predictions that define machine learning.

KEY RESPONSIBILITIES
• Design, implement and deliver performant and scalable machine learning libraries.
• Perform computationally intensive tasks with large and complex data using distributed computing systems (CPUs, GPUs, TPUs, Cloud, etc.).
• Write and maintain high-quality, maintainable and modular code with concise documentation and continuous integration together with research scientists and engineers.
• Contribute to the design and implementation of models, tools and libraries to accelerate our research effort.
• Bridge the gap between the research and product teams by integrating new fundamental research into applied projects.

SKILLS AND EXPERIENCE
• M.S./Ph.D. degree in Computer Science, Machine Learning or related field.
• 2-5 years’ experience
• Experience using Deep Learning frameworks such as PyTorch, Tensorflow and/or Jax.
• Experience in developing and debugging in Python3 and in at least one other compiled language (e.g. C++).
• Strong Software engineering experience (Object-Oriented Programming, Unit Testing, Profiling, CI, Docker) via previous work or contributions to open source projects.
• Experience with high-performance computing methods and frameworks such as MPI, Ray (distribution on clusters of CPUs and accelerators)
• Experience with DevOps and cloud technologies GCP, Docker, Kubernetes.

NICE-TO-HAVES
• Reinforcement Learning, Computer Vision, or Natural Language Processing experience.
• Structural biology or molecular dynamics experience.
• Published scientific papers in domains in relation with Artificial Intelligence and/or BioInformatics

Right to work in the United States is mandatory.
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Lead Machine Learning Engineer at Robert Half Technology

Location: Boston

Description

Robert Half is looking for a Lead Machine Learning/Computer Vision Engineer to join an early stage proptech startup here in Boston. They use cutting-edge artificial intelligence and computer vision to convert everyday real estate photos into actionable data. This is an opportunity to get on the ground floor with a fast-paced team delivering revolutionary solutions to a long-established industry.

Responsibilities:
• Identify, acquire, generate, process and/or prepare relevant datasets.
• Research and develop AI/DL/ML algorithms to solve challenging computer vision tasks
• Validate algorithms and/or models in a mathematically disciplined and statistically meaningful manner.
• Productionize algorithms to solve business problems.
• Develop clear, commented and understandable code for integration into production systems.
• Generate and present analysis results and reports tailored to target audience (scientists, software engineers, business strategists, investors, etc.).
• Collaborate with fellow product engineers to put the AI model in product pipeline and implementation.
Qualifications:
• 7+ years of experience with deep learning and computer vision. Experience with application in a product that has been commercialized.
• The ability to research and develop novel algorithms to solve cutting edge computer vision problems, such as semantic segmentation, object recognition, image/video understanding, product recommendation, Approximate Nearest Neighbor/ KNN indexes, photogrammetry, and SLAM.
• Strong background in applied mathematics, statistics and probability.
• Deep familiarity with latest Deep Learning and Computer Vision techniques and libraries.
• Deep familiarity with Python, AWS, Docker, and comfortable with deep learning frameworks like pytorch, tensorflow, and keras
• Deep familiarity in handling and processing images.

Requirements Python, Python Flask, TensorFlow, TensorFlow, Keras, Applying Machine Learning, Machine Learning, Machine Learning Algorithms, Machine Learning Libraries, Machine Learning Methods, Amazon Web Services (AWS)
Technology Doesn’t Change the World, People Do.

Robert Half is the worlds first and largest specialized talent solutions firm that connects highly qualified job seekers to opportunities at great companies. We offer contract, temporary and permanent placement solutions for finance and accounting, technology, marketing and creative, legal, and administrative and customer support roles.

Robert Half puts you in the best position to succeed by advocating on your behalf and promoting you to employers. We provide access to top jobs, competitive compensation and benefits, and free online training. Stay on top of every opportunity even on the go. Download the Robert Half app () and get 1-tap apply, instant notifications for AI-matched jobs, and more.

Questions? Call your local office at 1.. Robert Half will consider qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. All applicants applying for U.S. job openings must be authorized to work in the United States. Benefits are available to temporary professionals. Visit for more information.

2022 Robert Half. An Equal Opportunity Employer. M/F/Disability/Veterans. By clicking Apply Now, youre agreeing to Robert Halfs Terms of Use () .
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Lead Machine Learning Engineer (Remote-Eligible) at Capital One

Location: Boston

11 West 19th Street (22008), United States of America, New York, New York

Lead Machine Learning Engineer (Remote-Eligible)

As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

C4ML

The Center for Machine Learning (C4ML) is devoted to transforming how we work and making Capital One a leader in machine learning, artificial intelligence, and other areas of emerging technology. The ML Tools team within C4ML drives efficiency across the enterprise by building the right libraries, standards, and shared components that enable data scientists and MLEs to build and scale impactful models in a well-governed, well-architected way.

What you ll do in the role:
• The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you’ll be expected to perform many ML engineering activities, including one or more of the following:
• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
• Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation).
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.

Capital One is open to hiring a Remote Employee for this opportunity.

Basic Qualifications:
• Bachelor s degree
• At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
• At least 4 years of experience programming with Python, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:
• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• 3+ years of experience building production-ready data pipelines that feed ML models
• 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 2+ years of experience with container ecosystem technologies such as Docker
• 2+ years of experience with distributed computing technologies such as Spark, Dask, Ray
• 1+ years of experience with container orchestration technologies such as Kubernetes, ECS
• 2+ years of experience with data gathering and preparation for ML models
• 2+ years of people leader experience
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4; New York City s Fair Chance Act; Philadelphia s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
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Data Science & Machine Learning Engineer at Santander US

Location: Boston

Data Science & Machine Learning Engineer

Req ID: Req Date posted 07/22/2022

Data Science & Machine Learning Engineer

Boston, United States of America

WHAT YOU WILL BE DOING

The Senior Associate, Data Science drives cross functional analytics projects from beginning to end, builds relationships with partner teams, frames and structures questions, collects and analyzes data, and summarizes key insights in support of decision making. S//he works with engineers to evangelize data best practices and implement analytics solutions.
• Provide the essential synthesis of deep knowledge of MLOps and cloud services with data science fundamentals to help our automation efforts.
• Drive cross functional projects from beginning to end to help automate the ML infrastructure for rapid model development and testing, connecting those models to a variety of model serving platforms including ranking and streaming systems.
• Work with our IT, data engineering and data science teams to expand our architecture to access data staged from multiple data sources and/or systems to build, deploy or publish machine learning models that run efficiently in cloud pipelines.
• Design and implement pipelines to provide real-time data quality and model performance monitoring for timely interventions and ongoing assessment.
• Design and implement model management systems to effectively implement MLOps for banking and financial models.
• Translates business queries into actionable and commercial insights leveraging unstructured data and statistically robust techniques.
• Drives cross functional analytics projects from beginning to end, builds relationships with partner teams, frames and structures questions, collects and analyzes data, and summarizes key insights in support of decision making.
• Works with engineers to evangelize data best practices and implement analytics solutions.
• Evaluation and discovery of alternative data vendors including ability to quantifiably validate external algorithms and apply insights to commercially driven use cases.
• Performs quantitative analysis, including alpha assessment, risk analysis, portfolio construction and return attribution to enhance investment strategies using sourced and external data.
• Collaborates across functional areas of our business at every level of seniority to uncover and address opportunities for scalability and growth.
Qualifications:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Education:
• Bachelor’s Degree or equivalent work experience in Statistics, Computer Science, Physical Sciences, Economics, or an equivalent technical field (required)
• Master’s Degree in Statistics, Computer Science, Physical Sciences, Economics, or an equivalent quantitative field. (preferred)
Experience:

4+ yearsinData mining/advanced analytics applied to large-scale data-intensive projects.

Skills:
• Minimum of 4+ years non-internship professional experience developing business problem related statistical/ML modeling with industry tools.
• Minimum of 4+ years of hand-on working experience with structured programming languages and modern machine learning libraries, frameworks, and technologies including Python or R, SQL, etc.
• Minimum 4+ years of experience working with cloud services/platforms, Google, Azure and/or AWS
• Experience with Snowflake/Databricks or similar platform. Working experience with model registry will be desirable.
• Ability to adapt to various programming languages and environments.
• Knowledge of the principles of machine earning, classification models, time series regression and stochastic statistics to deliver improved business performance.
• Demonstrated ability to communicate complex concepts.
• Strong quantitative and problem-solving skills with focus hypothesis formulation and testing.
• Individually motivated and possess sound judgment, integrity, and a solid work ethic.
• Ability to clearly communicate complex results to technical and non-technical audiences.
• Ability to utilize analytics in a collaborative manner across business functions and product lines to derive optimum solutions.
• Experience with banking/financial system is preferred
At Santander, we value and respect differences in our workforce and strive to increase the diversity of our teams. We actively encourage everyone to apply.

Santander is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, genetics, disability, age, veteran status or any other characteristic protected by law.

Working Conditions:

Frequent Minimal physical effort such as sitting, standing and walking. Occasional moving and lifting equipment and furniture is required to support onsite and offsite meeting setup and teardown.

Employer Rights:

This job description does not list all of the job duties of the job. You may be asked by your supervisors or managers to perform other duties. You may be evaluated in part based upon your performance of the tasks listed in this job description. The employer has the right to revise this job description at any time. This job description is not a contract for employment and either you or the employer may terminate at any time for any reason.

Masters of Science (MS) English

Primary Location: Boston, Massachusetts, United States of America

Other Locations: Massachusetts-Boston

Organization: Santander Bank N.A.

As a part of our commitment to the health and safety of our employees and clients, we have implemented COVID-related health and safety requirements for our workforce. These requirements may include all or some combination of: disclosing your vaccination status, being fully vaccinated, regular testing, mask wearing and social distancing. As you go through our selection process, the requirements will be clearly disclosed to you.

Santander is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, genetics, disability, age, veteran status or any other characteristic protected by law.

US Candidates/Employees: Click here to view the EEO is the Law () poster and supplement and the Pay Transparency Policy Statement. ()

Click here to view the California Privacy Notice. Need assistance? Contact

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Machine Learning Engineer (Remote Opportunity) at REGIONS BANK

Location: Boston

Thank you for your interest in a career at Regions. At Regions, we believe associates deserve more than just a job. We believe in offering performance-driven individuals a place where they can build a career — a place to expect more opportunities. If you are focused on results, dedicated to quality, strength and integrity, and possess the drive to succeed, then we are your employer of choice.

Regions is dedicated to taking appropriate steps to safeguard and protect private and personally identifiable information you submit. The information that you submit will be collected and reviewed by associates, consultants, and vendors of Regions in order to evaluate your qualifications and experience for job opportunities and will not be used for marketing purposes, sold, or shared outside of Regions unless required by law. Such information will be stored in accordance with regulatory requirements and in conjunction with Regions Retention Schedule for a minimum of three years. You may review, modify, or update your information by visiting and logging into the careers section of the system.

Job Description:

At Regions, the Machine Learning Engineer (MLE) supports the Data and Analytics organization by designing, customizing, and implementing data science platforms for the development and production of machine learning models. The MLE will use machine learning knowledge and software architecture expertise to design promotion pipelines, implement dev/ops capabilities for machine learning models, and design processes for ensuring provenance across training and inference. The MLE is a forward thinking and visionary role, and will be a key leader in developing and supporting Regions model lifecycle infrastructure strategy.

Primary Responsibilities
• Designs and implements model deployment strategies
• Promotes Regions cloud strategy and design cloud-native machine learning workflows
• Develops tooling to facilitate model development, deployment, and monitoring of data products
• Develops automated workflows for machine learning pipelines
• Collaborates with data engineers to develop data and model pipelines
• Creates RESTful application programming interface (APIs)for streamlining, monitoring, and reporting on the model lifecycle
• Designs and implements deployment infrastructure
• Pushes best practices in model operations
• Helps contribute to a collaborative, open developer environment
• May provide advice and guidance to junior associates on occasion
This position is exempt from timekeeping requirements under the Fair Labor Standards Act and is not eligible for overtime pay.

Requirements
• Bachelor’s degree in Computer Science or a quantitative field
• Four(4) years of experience
• Experience with big data and machine learning tools such as Spark, HBase, Hive, Kubeflow, and Airflow
• Working knowledge of machine learning models
Preferences
• Master’s degree
Sills and Competencies
• Demonstrated experience with software engineering best practices and implementing software development lifecycles.
• Demonstrated success in one or more of the following programming languages: Python, Golang, Java, JavaScript, Rust and Scala
• Experience developing RESTful APIs
• Experience with Docker/Kubernetes

Position Type

Full time

Compensation Details

Pay ranges are job specific and are provided as a point-of-market reference for compensation decisions. Other factors which directly impact pay for individual associates include: experience, skills, knowledge, contribution, job location and, most importantly, performance in the job role. As these factors vary by individuals, pay will also vary among individual associates within the same job.

The target information listed below is based on the national range and level of the position.

Job Range Target:

Minimum:

$75,382.50 USD

Median:

$113,610.00 USD

Incentive Pay Plans:

This job is not incentive eligible.

Benefits Information

Regions offers a benefits package that is flexible, comprehensive and recognizes that “one size does not fit all” for associates. Listed below is a synopsis of the benefits offered by Regions for informational purposes, which is not intended to be a complete summary of plan terms and conditions.
• Paid Vacation/Sick Time
• 401K with Company Match
• Medical, Dental and Vision Benefits
• Disability Benefits
• Health Savings Account
• Flexible Spending Account
• Life Insurance
• Parental Leave
• Employee Assistance Program
• Associate Volunteer Program
Please note, benefits and plans may be changed, amended, or terminated with respect to all or any class of associate at any time. To learn more about Regions benefits, please click or copy the link below to your browser.

Location Details

Riverchase OPS Center

Location:

Hoover, Alabama

Bring Your Whole Self to Work

We have a passion for creating an inclusive environment that promotes and values diversity of race, color, national origin, religion, age, sexual orientation, gender identity, disability, veteran status, genetic information, sex, pregnancy, and many other primary and secondary dimensions that make each of us unique as individuals and provide valuable perspective that makes us a better company and employer. More importantly, we recognize that creating a workplace where everyone, regardless of background, can do their best work is the right thing to do.

OFCCP Disclosure: Equal Opportunity Employer/Disabled/Veterans
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Staff Machine Learning Engineer, Senior Software Engineer at Chewy

Location: Boston

Our Opportunity:

Chewy is looking for a Staff Machine Learning engineer to join a science driven team in supply chain charged with delivering state-of-art ML models helping all pet parents and people.

In this role, you will lead development and deployment of our critical Machine learning and deep learning models, which includes guiding data scientists, platform engineers in the delivery of the models. This role will involve execution, strategy, partnership, architecture, mentoring, and more. You have high standards and will take pride in Chewy like we do as well as push us to be better. You have delivered challenging technical solutions at scale, with a particular focus in using machine learning techniques to drive business and customer impact. You are equally happy talking about deep learning and software engineering, as you are brainstorming about continuous improvement and technology career development.

What You’ll Do:
• Solve impactful, large-scale ML problems and take the solutions from planning to production.
• Ideate and implement advanced ML solutions like domain-specific embeddings, custom featurization, and customized algorithms.
• Build a great company-wide ML platform that enables other data scientists and ML engineers to train, validate, deploy, and monitor ML
• Mentor teammates in advanced ML and ML engineering practices
• Engage with engineering leadership across Chewy to define development and production processes for ML creation and deployment.
• Recommend architectural patterns; e.g., consult on the architectural design of ML pipelines for collecting data for ML training and inference.
• Collaborate with a distributed team, including pairing, code reviews, identifying opportunities for code refactoring, and defining best practices.
What You’ll Need:
• 8+ years of recent professional industry experience in data science/software engineering
• 6+ years writing production-level, scalable code (e.g. Python, Scala)
• Expertise in machine learning/Deep Learning and statistical modeling
• Excited to answer product/engineering questions with data
• Strong communication and collaboration skills
• Ability to write technical papers and present results to both technical and non-technical audiences
• Driven to proactively help their teammates and Indeeds products
• Experience designing and conducting complex projects
Bonus:
• Ph.D. (preferred) or M.S. in a quantitative field (e.g., Quantitative Social Science, Computer Science, Statistics, Applied Mathematics, Physics, Machine Learning)
• Are familiar with recent developments in deep learning & machine learning, especially in time series, anomaly detection, NLP, explainability and interpretability, and the intersection thereof
• Have full stack experience in data collection, aggregation, analysis, visualization, productionization, and monitoring of data science products
• Are proficient in small data modeling work: Python, R, Julia, Octave
• Are proficient in big data modeling work: Hadoop, Pig, Scala, Spark
• Can fish for data: SQL, Pandas, MongoDB
• Deploy data science solutions: Java, Python, C++
• Communicate concisely and persuasively with technical and non-technical audiences
Chewy is committed to equal opportunity. We value and embrace diversity and inclusion of all Team Members.

If you have a disability under the Americans with Disabilities Act or similar law, or you require a religious accommodation, and you wish to discuss potential accommodations related to applying for employment at Chewy, please contact .

To access Chewys Privacy Policy, which contains information regarding information collected from job applicants and how we use it, please click here: ).
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Distinguished Machine Learning Engineer- Remote Eligible at Capital One

Location: Boston

Locations: VA – Richmond, United States of America, Richmond, Virginia

Distinguished Machine Learning Engineer- Remote Eligible

Distinguished Machine Learning Engineer

(Director-level)

At Capital One, we believe that machine learning represents the biggest opportunity in financial services today, and is a chance to revolutionize the industry. Capital One s commitment to machine learning has sponsorship from the CEO, the Board of Directors, and the executive committee of the company. The Center for Machine Learning is at the heart of this effort, and is leading the way towards building responsible and impactful tools, platforms, and solutions that leverage ML.

As a Capital One Machine Learning Engineer, you’ll be providing technical leadership to engineering teams dedicated to productionizing machine learning applications and systems at scale. You ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You ll serve as a technical domain expert in machine learning, guiding machine learning architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications. You’ll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You ll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology.

What you ll do in the role:
• Deliver ML models and software components that solve challenging business problems in the financial services industry, working in collaboration with the Product, Architecture, Engineering, and Data Science teams.
• Drive the creation and evolution of ML models and software that enable state-of-the-art intelligent systems.
• Lead large-scale ML initiatives with the customer in mind.
• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale.
• Optimize data pipelines to feed ML models.
• Use programming languages like Python, Scala, C/C++.
• Leverage compute technologies such as Dask and RAPIDS
• Evangelize best practices in all aspects of the engineering and modeling lifecycles.
• Help recruit, nurture, and retain top engineering talent.

Basic Qualifications
• Bachelor s degree.
• At least 10 years of experience designing and building data-intensive solutions using distributed computing.
• At least 6 years of experience programming in C, C++, Python, or Scala.
• At least 3 years of experience with the full ML development lifecycle using modern technology in a business critical setting.
• At least 2 years of experience using Dask, RAPIDS, or in High Performance Computing
• At least 2 years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn)

Preferred Qualifications
• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
• 3+ years of experience designing, implementing, and scaling production-ready data pipelines that feed ML models.
• 8+ years of experience within a large/data-intensive multi-line business environment.
• Experience partnering with technology peers responsible for data architecture and distributed computing infrastructure/platforms.
• Ability to communicate complex technical concepts clearly to a variety of audiences.
• ML industry impact through conference presentations, papers, blog posts, or open source contributions.
• Ability to attract and develop high-performing software engineers with an inspiring leadership style.

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

No agencies please. Capital One is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4; New York City s Fair Chance Act; Philadelphia s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One’s recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
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Senior Machine Learning Engineer at Cohere Health

Location: Boston

Company Overview

Cohere Health is illuminating healthcare for patients, their doctors, and all those who are important in a patient’s healthcare experience, both in and out of the doctors office. Founded in August, 2019, we are committed to eliminating wasteful friction patients and doctors experience in areas that have nothing to do with health and treatment, particularly for diagnoses that require expensive procedures or medications. To that end, we build software that is expressly designed to ensure the appropriate plan of care is understood and expeditiously approved, so that patients and doctors can focus on health, rather than payment or administrative hassles.

Opportunity Overview

In this role, you’ll join our growing team of world-class engineers, statisticians, and clinical experts to deploy machine learning algorithms that help automate burdensome administrative clinical practices. You will be tasked with finding the most promising opportunities for impact and then delivering on them.

Our ML team’s work is focused in the following four areas:
• Information retrieval from unstructured clinical text
• Predicting clinical findings from structured and unstructured data sources
• Building intelligent algorithms for ordering work queues
• Identifying anomalies, such as behavior change and gaming, in user behavior

Last but not least: People who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.

What you will do:
• Perform in-depth analysis of healthcare data coupled with data from product and other sources to independently design, develop, and deliver ML models.
• Build reliable and scalable production machine learning systems
• Work on feature engineering, statistical analysis, developing novel ML techniques, understanding model performance, and ensuring fit-for-purpose.
• Work cross-functionally across diverse stakeholders, including product managers, statisticians, EHR data specialists and physicians.
• Optimize algorithms, running in real-time, for speed and accuracy.

What you will have:
• You have 3+ years experience in applied ML in the industry with a degree or higher (MS/PhD) in computer science, machine learning, mathematics or similar field
• Clear understanding of model building, model maintenance and the measures that optimize models for product use
• Understand experimental design and can independently perform collection, measurement, and interpretation of results
• Expert in Python or other common analytical data tools
• Experienced in various regression and classification approaches
• Hands on experience building NLP models, using a variety of techniques

Bonus points for:
• Experience with ElasticSearch
• Experience with healthcare data such as claims and EMR data
• Experience with OCR
• Experience with graph databases or network analysis
• Experience building ranking or recommender systems
• Hands on experience using AWS tools such as SageMaker Studio and Neptune
• Experience with TensorFlow is also a plus

We can’t wait to learn more about you and meet you at Cohere Health!

Equal Opportunity Statement

Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all. To us, it’s personal.
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Staff Machine Learning Engineer at Wayfair

Location: Boston

Who We Are

is a leader in the e-commerce space for all things home. Wayfairs community of Data Scientists and Machine Learning Engineers are obsessed with using data and technology to help our customers build a home that they love. Our technology platforms support millions of searches for the perfect item every day, providing a top-of-class purchasing and delivery experience. Come help us innovate and grow to our next $10B in revenue.

We are looking for an experienced machine learning engineer interested in partnering with data scientists, product managers, software engineers, and cross-functional business partners (e.g. marketing, website, B2B, pricing, search and recommendation) to drive and expand Wayfairs state-of-the-art customer identity products. This includes but is not limited to operationalizing and scaling advanced statistical and machine learning models to power probabilistic device, person, and household graphs at Wayfair and researching new clustering, feature engineering, and predictive modeling techniques to extract insights with more accuracy and granularity.

Were looking for someone who not only enjoys solving ambiguous scientific problems, writing code and building ML models in production, but is also able to upskill engineers, data scientists, and business leaders around them through leading by example. In this role, you will be driving cutting-edge machine learning and statistical research to continuously improve the accuracy and robustness of probabilistic identity products, increase the recognition of and reach to Wayfair customers, increase the computational efficiency of the production pipeline, and empower the performances of various downstream products, such as personalization and recommendation services, marketing attribution, and online AB experimentation platforms.

What You’ll Do
• Lead the research and development of machine learning models and pipelines to improve the accuracy and efficiency of identity recognition at Wayfair.
• Develop scalable identity products by leveraging Google Cloud native technologies.
• Drive identity integrations & align with key stakeholders across various products and platforms.
• Work with software engineers to productionalize machine learning outputs for real-time consumption via graph database structures.
• Think outside of the current technology/stack limitations to push the boundaries on what is possible and deliver feasible solutions collaboratively.
• Promote a culture of machine learning and data science excellence by participating in weekly research, learning, and development sharing sessions.

What You’ll Need
• Advanced degree (Master or PhD) in Machine Learning, Computer Science, Engineering, Statistics, or a related quantitative field.
• 3+ years of experience in advanced machine learning and statistical modeling, including hands-on designing and building production models at scale.
• Familiarity with ML model development frameworks, ML orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Python, and SQL.
• Excellent organizational, analytical, and hypothesis- driven critical thinking skills to identify business opportunities and transform data into actionable insights.
• Excellent communication skills to explain complex data science and machine learning concepts/ideas/methods to technical and business audiences.

Nice to Have
• Mix of start-up and large-company experience working on data science and machine learning.
• Familiarity with Machine Learning platforms offered by Google Cloud and how to implement them on a large scale (e.g. BigQuery, GCS, Dataproc, AI Notebooks).
• Direct experience leading research around customer identification.
• Familiarity with web development, cookie usage, HTTP protocols, and consumer privacy laws.
• Experience developing and applying innovative machine learning methodologies to tackle real-world identity challenges (e.g. customer device mappings, person & household graphs) and translating technical results to business objectives and impacts
• Experience with graph databases, such as TigerGraph.
About Wayfair Inc.

Wayfair is one of the worlds largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, were reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If youre looking for rapid growth, constant learning, and dynamic challenges, then youll find that amazing career opportunities are knocking.

No matter who you are, Wayfair is a place you can call home. Were a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair and world for all. Every voice, every perspective matters. Thats why were proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.

We are interested in retaining your data for a period of 12 months to consider you for suitable positions within Wayfair. Your personal data is processed in accordance with our Candidate Privacy Notice (which can found here ). If you have any questions regarding our processing of your personal data, please contact us at . If you would rather not have us retain your data please contact us anytime at .
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