Fulltime Machine Learning Engineers openings in New York, United States on September 22, 2022

Machine Learning Engineer at Jeeng

Location: New York

You will help Jeeng apply state-of-the-art machine learning for real-time bidding at scale. You will contribute to the full stack of machine learning development: from analyzing large datasets of user events, building training datasets, feature engineering, model tuning, automating model retraining, and deploying into production.

Specific Goals
• Analyze large-scale user event data to identify areas of improvement for Jeeng’s machine learning
• Run machine learning modeling from experiment hypothesis through to live real-time bidding
• Apply data and feature engineering to expand the signals available for machine learning training and real-time inferencing
• Report on machine learning experiment results
• Keep documentation on machine learning systems up-to-date
• Collaborate with product management, business representatives, and other software engineers to identify areas for machine learning innovation

Requirements:
• 5+ years of experience with Machine Learning and Data Science
• 3+ years Python software engineering experience
• Experience with advanced SQL
• Cloud development experience (AWS preferred)
• Experience deploying models into production systems
• Great communication skills and high standards

This is extra, but if you have it, it will make us happy
• Experience with Java or Scala
• Experience working remotely
• Knowledge of the digital and AdTech landscape
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Senior machine learning engineer at Rokt

Location: New York

Description

Rokt is the global leader in ecommerce technology, helping companies seize the full potential of every transaction moment to grow revenue and acquire new customers at scale.

Live Nation, Groupon, Staples, Lands’ End, Fanatics, UrbanStems, GoDaddy, Vistaprint and HelloFresh are among the more than 2,500 leading global businesses and advertisers that are using Rokt’s solutions to drive more value through every transaction by offering highly relevant messages to their customers at the moment they are most likely to convert.

With our December 2021 Series E raise of USD$325M, Rokt is expanding rapidly and globally operating in 19 countries across North America, Europe and the Asia-Pacific region with the largest office in NYC and a major R&D hub in Sydney.

With annual revenues of more than US$200M and vibrant company culture, Rokt has been listed in Great Places to Work’ in the US and Australia.

Our award-winning culture is guided by our five core values : Smart with Humility, Own the Outcomes, Force for Good, Conquer New Frontiers, and Enjoy the Ride.

These values help us attract, engage, and develop the right talent around the globe and ensure we have the right conditions to do our best work.

Keen to join a fast-growing company and a vibrant culture? Learn more at rokt.com.

The Rokt engineering team builds best-in-class ecommerce technology that provides personalized and relevant experiences for customers globally and empowers marketers with sophisticated, AI-driven tooling to better understand consumers.

Our bespoke platform handles millions of transactions per day and considers billions of data points which give engineers the opportunity to build technology at scale, collaborate across teams and gain exposure to a wide range of technology.

We are expanding rapidly in our major R&D centers in NYC and Sydney. We are passionate about using intelligent systems to improve the transaction moment for retailers everywhere.

Come join us and build the future!

The Role

As a Senior Machine Learning Engineer you are someone who has significant expertise in modelling, statitics and programming.

You will be working with our engineering and product teams to design, build and productionize proprietary machine learning models to solve different business challenges including smart bidding, lookalike modelling, forecasting, and etc.

Responsibilities
• Collaborate closely with product managers and other engineers to understand business priorities, frame machine learning problems, architect machine learning solutions.
• Build and productionize machine learning models including data preparation / processing pipelines, machine learning orchestrations, improvements of services performance and reliability and etc.
• Contribute and maintain the high quality of code base with tests that provide a high level of functional coverage as well as non-functional aspects with load testing, unit testing, integration testing, etc.
• Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices.
• Mentor other team members, facilitate within / across team workshops and lead the agile development.

Requirements
• Bachelor’s degree in Computer Science, a similar technical field of study or equivalent practical experience.
• 5+ years of industry experience in building production-grade machine learning systems with all aspects of model training, tuning, deploying, serving and monitoring.
• 2+ years of industry experience in software engineering roles and development experience in Python, SQL, and / or other programming languages.
• Strong understanding in software engineering best practices
• Knowledge in at least one of following areas – Bayesian methods, Econometrics, Reinforcement learning, Gradient boosting machine, Natural language processing, Computer vision, etc.
• Be motivated, self-driven in a fast (we truly mean fast) paced environment with a proven track record demonstrating impact across several teams and / or organizations.
• Ability to communicate and collaborate effectively with business stakeholders and manage tasks in a timely manner.
• At Rokt we encourage autonomy; teams have complete ownership of their systems including building, running and monitoring.

As such, you may be required to be on-call and respond to systems alerts should they arise.
• Ideas, opinions, and the ability to share them through respectful proposals, presentations, and team-wide discussions, An eagerness to work and learn in the open and share your learnings with your teammates.
• Experience in DevOps, MLOps and SRE is a massive plus.
• Experience of Kubernetes, Kubeflow, TFX and Feature Store in a production environment is a massive plus.

Benefits

Force for Good. We actively invest in the growth of our people and the strengthening of our communities. Our NYC office is 100% vaccinated to keep our employees and community safe and healthy.

We require all Rokt’stars as well as anyone else who will be onsite at the Rokt NYC office clients, contractors, vendors, and suppliers to show proof of vaccination and their booster shot.

BEETROOT IS NY OFFICE ONLY
• Work with the greatest talent in town. Our recruiting process is tough. We hold a high bar because we have a high-performing, high-velocity culture – we only want the brightest and the best.
• Join a community. We believe the best things happen when we come together to solve complex problems and make meaningful connections with each other through interest groups, sports clubs, and social events.
• Accelerate your career. Develop through our global training events, Level Up’ investment, online training courses, and our fantastic people leaders.

Take your career to Rokt’speed – Grow your career in our rapidly growing company.

Take a break. When you work hard, we know you also need to rest. We offer generous time off and parental leave policies, as well as mental health and wellness days for all employees.

We also offer a paid Rokt’star Sabbatical for employees who have been with us for 3 years or more.

Stay happy and healthy. Enjoy catered lunch 3 times a week and healthy snacks in the office. Plus join the gym on us! In the US, access generous retirement plans like a 4% dollar-for-dollar 401K matching plan and get fully funded premium health insurance for your whole family.

And our NYC office is dog-friendly! BEETROOT IS NY OFFICE ONLY
• Become a shareholder. All Rokt’stars have stock options. If we succeed, everyone enjoys the upside.
• See the world! Along with our global all-staff events in amazing locations (Phuket, Thailand in January 2020, Hawaii in May 2022), we also offer generous relocation packages for those interested in moving to another Rokt office.

We have cool offices in great cities – New York, Sydney, London, Singapore, Tokyo.

Get the best of both worlds with a hybrid workplace. We currently work 3 days a week in office, allowing you to enjoy the best of both worlds (please note : this is subject to change based on the needs of the business and some support roles still require a full time presence).

One week per quarter, you also have the flexibility to work from anywhere.

We believe in equality. Rokt is an Equal Opportunity Employer and recognizes that a diverse workforce is crucial to our success as a business.

We would love you to apply for one of our open roles – irrespective of socio-economic status or background, age, gender identity, race, religion, sexual orientation, color, pregnancy, carer / family responsibilities, national and social origin, political opinion, marital, veteran, or disability status.

Salary range : $200,000 – $300,000 / year

Last updated : 2022-09-22
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Manager, Machine Learning Engineer at Zip Co

Location: New York

Before we dive into the role, let’s talk about flexibility. At Zip, our office is in New York City but we can hire from anywhere across the United States. Our Zipsters can choose where and when they work by taking full advantage of our hybrid-work environment.

So whether you’re fully remote, mostly in the office or a mix of the two, you’ll be empowered to do whatever brings out your best.

About us

At Zip, previously Quadpay, we provide fair and seamless solutions that simplify how people pay with our leading Buy Now, Pay Later platform.

Focused on product innovation that puts people at the center, we’re here to do things differently. We are a responsible, digital alternative to the broken credit card model, providing consumers with a better way to manage their finances. We also help merchants and businesses to grow by offering them best–in–class products that improve conversion, increase basket sizes and delight their customers.

We’re a high-growth team with endless opportunities as we scale. Come and join the ZipFam!

About the role

The vision of the Machine Learning (ML) Engineering team at Zip is to drive and enable ML usage across the company, and at all stages of our product’s life cycle. You’ll be in charge of making that vision a reality as we fundamentally believe machine learning engineering is the engine of our world-class data science and will lead us as a company.

In this role, you will be the connective tissue between data engineering, data science, product, and software engineering. Supporting our Data Science teams in data sourcing, cleaning and access, FeatureStore, model development, and model observability. Build automation and productionisation, and provide ML Eng consultancy to all parties. You will work on cross-functional products and push the envelope on data and ML focused solutions.

What you’ll do
• Architecture: Own the vision for ML engineering in our company: the architecture of our platform and the technical approach to our solutions
• Play the player-coach role: guide and mentor your squad while keeping your hands on the keyboard and shipping out brilliant outcomes yourself
• Technically Deliver: Co-build our FeatureStore (utilized by multiple teams), serving capabilities, data quality, monitoring, cataloging, and the long list of additional capabilities
• Focus on efficiencies: Hone our DS model lifecycle and push to beat current SLAs
• Partner & Service: We’re stronger together, take the DS-ML partnership to new levels
• Be a Leader: Lead by example, out of humility, and make sure we stay true to our family values. Care for your team with a servant leadership mindset
• Be a Manager: Own project management, run a highly efficient team
• Be an active member of the Data Leadership Team, have a daily say on our direction and continuously evolve your leadership skills, together with your fellow leaders

What you’ll bring
• You’re a culture ADD: You believe in and want to participate in a blameless culture that focuses on process and technology
• You have worn the captain jersey before, leadership is not a new practice for you, it’s a skill you are in permanent pursuit to perfect
• You have a proven track record in ML engineering; designing and implementing ML systems, working in cloud environments and their infrastructure, tackling big picture initiative and feeling comfortable charting a path forward where there’s ambiguity
• Expertise with ML Ops, ML pipelines, algorithms, statistical methods, and analytics to solve real-world engineering problems
• Comfortable operating at all levels of the predictive stack and user behavior modeling including data collection, feature engineering, batch training and low-latency online serving
• Familiarity with Python development ecosystem and technologies like PySpark, Pandas, Jupyter notebooks
• You obsess over the concept of reliable “ML Ops” platform and believe in our mission of building the underlying foundation for every decision we make as a company
• You don’t sleep well at night when you leave work with a question unanswered. You feel accountable for everything you do, and it has been driving you your entire life
• You’re a builder of teams, a driver of positive culture, you encourage collaboration and spending time together as a team. You take pride in bringing a team together, daily
• You love learning new things: You know that there’s always more to learn, and it bothers you that there isn’t enough time in the day to learn about the next topic. You’re up-to-date on new trends in data – you know who’s using what to solve various problems and are excited for the next release of your favorite tool. If you can handle being thrown in the deep end of the pool, this team’s for you

Nice to have
• Sense of humor is hugely preferred.
• Past experience in the Financial industry
• Experience with ML platforms/vendors like Dataiku/H2O/etc.
• Experience with Feature Store design, development, and implementation
• Devops experience / Data Science experience
• Additional programming experience (Java/Scala/C#/etc.)
• Strong mathematical skills with knowledge of statistical methods
• An interesting life story / a cool hobby / a diverse background has proven to bring more to the table in terms of perspective, what’s yours?

Closing

We’re proud to be a values-led business. Our values form our Mamba mentality – how we’re better today than yesterday, and are used to create game-changing experiences for our customers and fellow Zipsters.

If you only meet some of the requirements for this role, that’s okay. We value a diverse range of backgrounds and ideas and believe this is fundamental for our future success. So, if you have the curiosity to learn and the willingness to teach what you know, we’d love to hear from you.

We pride ourselves on creating an inclusive workplace that provides equal opportunities to all persons regardless of their age, cultural background, sexual orientation, gender identity and expression, disability, veteran status, or anything else.

What’s in it for you?

We offer a variety of perks and benefits to support you at both work and home. Here’s a taste of what you can expect!

● Flexible working culture

● Share incentive programs

● 20 days PTO every year

● Generous paid parental leave

● Leading family support policies

● 100% employer covered insurance

● Beautiful Midtown office with a casual dress code

● Learning and wellness subscription stipend

● Company-sponsored 401k match

● Remote working allowance

Join us on our mission to be the first payment choice, everywhere and every day.
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Senior Manager, Machine Learning Engineering (Remote-Eligible) at Capital One

Location: New York

Center 1 (19052), United States of America, McLean, VirginiaSenior Manager, Machine Learning Engineering (Remote Eligible)

As a Capital One Senior Manager, Machine Learning Engineering, you’ll be leading 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.

What you’ll do in the role:

This 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.
• Hire, grow and retain top talent

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

Basic Qualifications:
• Bachelor’s degree
• At least 8 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 3 years of experience building, scaling, and optimizing ML systems
• At least 2 years of experience leading teams developing ML solutions
• At least 4 years of people management experience.

Preferred Qualifications:
• Master’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 3+ years of experience building production-ready data pipelines that feed ML models
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
• Experience in one of these ML workflow tools: Kubeflow, Argo Workflow Controller, Airflow or Prefect

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 4901-4920; 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 1-800-304-9102 or via email at (see below) . 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 (see below)

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 Scientist/Machine Learning Engineer- New York, NY at Bank of America

Location: New York

Job Description:

Responsible for designing and developing complex requirements to accomplish business goals. Ensures that software is developed to meet functional, non-functional, and compliance requirements. Ensures solutions are well designed with maintainability/ease of integration and testing built-in from the outset. Possess strong proficiency in development and testing practices common to the industry, and have extensive experience of using design and architectural patterns. At this level, specializations start to form in either Architecture, Test Engineering or DevOp. Contributes to story refinement/defining requirements. Participates and guides team in estimating work necessary to realize a story/requirement through the delivery lifecycle. Performs spike/proof of concept as necessary to mitigate risk or implement new ideas. Codes solutions and unit tests to deliver a requirement/story per the defined acceptance criteria and compliance requirements. Utilizes multiple architectural components (across data, application, business) in design and development of client requirements. Assists team with resolving technical complexities involved in realizing story work. Designs/develops/modifies architecture components, application interfaces, and solution enablers while ensuring principal architecture integrity is maintained. Designs/develops/maintains automated test suites (integration, regression, performance). Sets up and develops a continuous integration/continuous delivery pipeline. Automates manual release activities. Mentors other Software Engineers and coaches team on CI-CD practices and automating tool stack. Individual contributor.

Global Banking Technology – (GBT):
• Believes diversity makes us stronger so we can reflect, connect and meet the diverse needs of our clients and employees around the world
• Is committed to building a workplace where every employee is welcomed and given the support and resources to perform their jobs successfully
• Wants to be a great place for people to work and strives to create an environment where all employees have the opportunity to achieve their goals
• Provides continuous training and development opportunities to help employees achieve their career goals, whatever their background or experience
• Is committed to advancing our tools, technology, and ways of working to better serve our clients and their evolving business needs
• Believes in responsible growth and is dedicated to supporting our communities by connecting them to the lending, investing and giving them what they need to remain vibrant and vital

Responsibilities:
• Design and develop scalable ML/AI solutions to solve diverse business challenges by deriving features from rich data sources, training, evaluating and deploying models to production using cutting edge technologies
• Gather and analyze data to perform statistical analysis, identify key factors and build comprehensive visualizations to report findings
• Utilize statistical methods to process, clean and validate data for uniformity and accuracy
• Create and maintain end-to-end data pipelines and APIs according to business requirements
• Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems

Required Skills:
• 5+ years in a data science role with proven record of implementing end-to-end ML/AI solutions into production
• 5+ years of experience using statistical computer languages, such as R or Python (preferred)
• 3+ years of experience working with large data sets (> 1TB) and using big data solutions such as Hadoop, Hive, Spark, Storm, MongoDB etc.
• 1+ year of experience with deep learning (e.g., CNN, RNN, LSTM) and NLP frameworks
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, etc. and their real-world advantages/drawbacks
• Rigorous understanding of statistics and ability to discern appropriate statistical techniques to problem-solve
• Proficiency with writing SQL queries

Desired Skills:
• Master’s degree or PhD in computer science, applied mathematics, or related technical/scientific field
• Experience with data visualization tools, such as Tableau
• Prior work experience in the financial industry
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Software Engineer, Machine Learning at Meta

Location: New York

Meta is embarking on the most transformative change to its business and technology in company history, and our Machine Learning Engineers are at the forefront of this evolution. By leading crucial projects and initiatives that have never been done before, you have an opportunity to help us advance the way people connect around the world. The ideal candidate will have industry experience working on a range of recommendation, classification, and optimization problems. You will bring the ability to own the whole ML life cycle, define projects and drive excellence across teams. You will work alongside the world’s leading engineers and researchers to solve some of the most exciting and massive social data and prediction problems that exist on the web.

Software Engineer, Machine Learning Responsibilities:
• Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence
• Adapt standard machine learning methods to best exploit modern parallel environments (eg, distributed clusters, multicore SMP, and GPU)
• Re-evaluate the tradeoffs of already shipped features/ML systems, and you are able to drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate
• Leading a team from a technical perspective to develop ML best practices and influence engineering culture
• Be a go-to person to escalate the most complex online/production performance and evaluation issues, that require an in depth knowledge of how the machine learning system interacts with systems around it
• Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
• Suggest, collect and synthesize requirements and create effective feature roadmap
• Code deliverables in Tandem with the engineering team
Minimum Qualifications:
• 6+ years of experience in software engineering, or a relevant field. 4+ years of experience if you have a PhD
• 2+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical field
• Experience with developing machine learning models at scale from inception to business impact
• Knowledge developing and debugging in C/C+ and Java, or experience with Scripting languages such as Python, Perl, PHP, and/or Shell scripts
• Experience demonstrating technical leadership working with teams, owning projects, defining and setting technical direction for projects
• Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Preferred Qualifications:
• Masters degree or PhD in Computer Science or a related technical field
• Exposure to architectural patterns of large scale software applications
Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at (see below)
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Senior Machine Learning Engineer (Remote) at Jobot

Location: New York

Come join a Series A startup that is helping millions of people achieve financial wellness.

This Jobot Job is hosted by Brandon Bays

Are you a fit? Easy Apply now by clicking the “Apply” button and sending us your resume.

Salary $185,000 – $240,000 per year

A Bit About Us

We are a venture-backed fully-remote FinTech startup committed to helping millions of people achieve financial wellness while de-stigmatizing debt.

We are looking to hire a Senior Machine Learning Engineer who will play a huge role in our company as ML/AI is integral within our product to better understand users and create new products that help improve personal finances.

Why join us?

It is the perfect time to join our team as we recently received $15M Series A funding that is helping us grow and scale the product + remote team.

Benefits
• Competitive salary and stock options
• Medical, Vision and Dental Insurance
• 401 (k) with generous match
• Flexible and 100% remote work structure
• Computer provided
• WFH stipend
• Wellness reimbursement
• Unlimited PTO
• Unlimited Sick Time

Job Details

Qualifications For This Role
• 4+ years of machine learning product development experience and have a deep understanding of the best practices for ML systems
• 6+ years of experience in software engineering and development experience in Python, SQL, Go, and/or other programming languages
• Fluency in using a neural network framework such as TensorFlow, Keras, Caffe, PyTorch, Theano, or MXNet
• Ability to architect data pipelines using tools like Apache Beam or Spark
• You have experience with creating best practices for data organization-wide
• A track record of providing mentorship and technical leadership
• Ability to build APIs and libraries for Java, Scala, or Python
• Experience with data processing and storage frameworks like Google Cloud Dataflow, Hadoop, Scalding, Spark, Storm, Cassandra, Kafka, etc
• Work collaboratively with other engineers to understand business priorities and architect solutions to machine learning challenges

Interested in hearing more? Easy Apply now by clicking the “Apply” button.
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Machine Learning Engineer at Cubiq Recruitment

Location: New York

Role: Machine Learning Engineer

Specialism: Training and Inference

Location: US – East Coast & UK

We’re partnered with a global giant that is a challenger to some of the major social media platforms and they are looking to add creative and self-driven Staff or Principal Machine Learning Engineers to work on various projects at a massive scale with users well above 300M.

This is a unique opportunity to build a platform from the ground up (think Facebook in 2006).

To give you insight into the role, they currently support close to 300 million users on their platform who have come online in just the last few years and their vision for the product is to revolve around its algorithmically generated content feeds and ensuring users remain engaged and diverse as it grows on a massive scale.

From a team perspective, they operate in a free and experimental way, the major difference from their competitors is they allow staff & engineers complete freedom to conduct experiments by learning from both successes and failures to develop highly scalable and state-of-the-art algorithms that will be used by hundreds of millions of people globally.

We’re currently attracting subject matter experts from Facebook, Amazon, Apple & Spotify, and we’re keen to hear from candidates who’ve worked on similar projects scaling up large systems (all applications considered).

As part of the Training and Inference Team you will build and maintain the tools and services needed to scale ML models on state of the art hardware across the Platform. You will have free reign to experiment and deploy models at lightening speed.

The ML engineer will have a hands-on role in building common tools and services and deploying them across the platform, including inference clusters to streamline future research, and high quality reusable libraries.

Person Skills
• Ph.D/ MSc degree in Computer Science or related quantitative discipline
• Experience in training ML models with frameworks like PyTorch Serving: TFServing, Triton, TorchServe,Seldon 2 years of experience working on large systems at massive scale
• Excellent coding skills in at least one of Python, C/C++, Java, NodeJS, Go, Scala
• Experience working with Kubernetes/Kubeflow
• Experience with distributed systems, scalable data processing frameworks (e.g., Spark,Kafka) and noSQL systems (e.g., HBase, Cassandra) is a plus
• Good knowledge of GPU, TPU accelerators and GCP

On offer is an excellent package and, in most cases, we are beating current packages. For example, leading salaries, genuine share options in a company in hyper-growth mode, bonuses, health insurance, and more.

Please apply below with a copy of your resume, or contact Mat Holliday at Cubiq Recruitment on +44 (0) 161 214 3842 /

This company is an equal opportunity employer and value diversity. They do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

If you’re interested in finding out more about this opportunity, please submit your CV via the link provided and we will contact you shortly for a confidential discussion.
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Senior Machine Learning Platform and Ops Engineer at Apple

Location: New York

Posted: Mar 30, 2022

Role Number:200337424

At Apple, we work every day to create products that enrich people’s lives. Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads, App Store, and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy. The Machine Learning, Experimentation and Ad Serving team designs and builds best of breed systems for dealing with our complex and ever-growing platform needs that help deliver highly optimized advertising content to consumers. Are you a results-oriented and versatile engineer who can excel in an Agile environment? You will work closely with data scientists, work with other engineers to design, develop, and implement solutions, including leveraging open source, and building tools, frameworks, and components that will enable us to improve and scale our ML Platforms and model release lifecycle. The team is directly responsible for systems that are used by thousands of advertisers, publishers and developers and has high visibility in the mobile advertising space.

Key Qualifications
• Experience building and scaling systems both on premise and the cloud. Experience building large scale applications/services
• Experience with building AI/ML infrastructure, writing production level code, & deploying Machine Learning models to prod
• Experience working on complex problems and systems where scalability and performance are very important (every millisecond counts)
• Proven experience architecting, developing and deploying internet-scale, distributed and critical services
• Pride in building tools to automate routine tasks, organized & detailed
• Familiar with CI, CD & Deployment tooling
• Release engineering & release management experience
• Network, scaling, performance tuning & trouble-shooting
• Strong problem solving and debugging skills are required. Ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams
• Results oriented and deadline driven
• A desire to work in a fast-paced and challenging work environment
• Prior experience in advertising industry is a huge plus.

Description

ML Engineering, experimentation and serving team is the backbone of Apple’s Ad Platform. We are responsible for bringing numerous features to advertisers and consumers while simultaneously supporting continuous experimentation by the Data Science team. As a key contributor to this team, you will manage, design and develop secure and scalable back-end systems. You will enjoy high-performing, elegant systems from the ground up, in close partnerships with various teams. You will also possess keen judgment in selecting technologies and building the right solution for the interesting challenges we get to tackle here. Join us and contribute to a culture that emphasizes understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, and productivity. We are one team, nurturing each other’s growth and supporting each other in delivering for our customers and Apple!

Education & Experience

You’ve earned a: (a) PhD in Computer Science with experience building production systems, or (b) MS in CS with 2+ years of experience in working with large data projects with at least 1 year building software/ml platforms, or (c) BS in CS with 4+ years of experience in the industry with at least 2 year building software/ml platforms.

Additional Requirements
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Senior machine learning engineer at Capital One

Location: New York

Locations : VA – McLean, United States of America, McLean, VirginiaSenior 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.

As a Senior Machine Learning Engineer and part of our Center for Machine Learning (C4ML) line of business, you will be joining a team of experienced Machine Learning Engineers that support, build, and enable Machine Learning capabilities across the organization.

As a Model Development Libraries team member you will work closely with internal customers and infrastructure teams (Enterprise Model and Feature Platform) to help ensure Models and Tools being developed meet our Standards and Best Practices.

You will be able to further expand your knowledge and develop your expertise in modern Machine Learning frameworks, libraries and technologies while working closely with internal stakeholders to understand the evolving business needs.

If you have a penchant for creative solutions and enjoy working in a hands-on, collaborative environment, then this role is for you.

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 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications : 1+ years of experience building, scaling, and optimizing ML systems1+ years of experience with data gathering and preparation for ML models2+ years of experience developing performant, resilient, and maintainable codeExperience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud PlatformMaster’s or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigmsContributed to open source ML software Authored / co-authored a paper on a ML technique, model, or proof of concept3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance 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 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act;

com. 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 Careers capitalone.comCapital 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).

Last updated : 2022-09-22
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