Uber is looking for a Computer Vision Engineer in Seattle – Apply Here!

Deal Score0
Deal Score0

About the role:
Partners with stakeholders to design, develop, optimize, and productionize machine learning (ML) or ML-based solutions and systems that are used within a team to solve complex problems with multiple dependencies. This role also leads team efforts to leverage and improve ML infrastructure for model development, training, deployment needs and scaling ML systems.
About the Team:
Our crew manifests AI and machine learning to be maximally impactful at Uber by pushing the frontiers of research, developing high quality scalable platforms, and collaborating on innovative applications. To further this mission, the group brings together AI-focused engineering, product, and research teams under a single umbrella to ensure cutting-edge AI innovation is rapidly transferred into company-wide platforms, accelerating Uber’s positive impact on the world.
Our team within Uber is building Uber’s computer vision platform to democratize the technology at Uber. We are rapidly growing, and are responsible for developing state of the art computer vision and machine learning solutions to derive inferences from image/video data on our platform that directly drive efficiencies across the company. In doing so, we are aiming to revolutionize transportation. We believe it is important to be able to adapt easily to meet the fast pace of a rapidly evolving research, development, and testing environments. Here we rub shoulders with world class scientists and engineers and we use our skills to solve some of the toughest problems in the geo-spatial domain using innovative compute infrastructure and tools. This unit at Uber is looking for adaptable computer vision/machine learning experts who are not afraid to get their hands dirty with real world issues to work on impactful problems.
Our group may be right for you if you:
• have a good balance of theoretical knowledge and programming expertise.
• thrive on applying their knowledge, learning new technologies and don’t believe in one-size-fits-all solutions.
• strive to prove that speed and quality are not conflicting – i.e. that both can be achieved at the same time.
• feel ownership on everything they ship to production – i.e. code or design is not “released” until completion is verified confidently.
• think a working proof-of-concept is the best way to make a point.
• pride themselves on efficient monitoring, strong documentation, and proper test coverage.
• live on the edge between research and engineering, especially in areas like machine learning and computer vision
• like not just inventing new algorithms, but seeing them all the way into devices that move through the real world
• believe that the whole is greater than the sum of its parts.
• i.e. the candid feedback of others is fuel for continuous improvement.
Minimum qualifications:
• PhD or equivalent in Computer Science, Engineering, Mathematics or related field OR 3-years full-time Software Engineering work experience, WHICH INCLUDES 2-years total technical software engineering experience in one or more of the following areas:
• Programming language (e.g. C, C++, Java, Python, or Go)
• Training using data structures and algorithms
• Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
• Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
• Note the 2-years total of specialized software engineering experience may have been gained through education and full-time work experience, additional training, coursework, research, or similar (OR some combination of these). The years of specialized experience are not necessarily in addition to the years of Education & full-time work experience indicated.
Technical skills:
• Experience developing Computer Vision algorithms
• Masters in EE, CS or related fields.
• Expertise with computer vision and/or machine learning, especially deep learning.
• Familiarity with deep learning frameworks such as Tensorflow, Keras, Pytorch.
• Ability to productionize and/or machine learning solutions in context of other machine learning systems and the larger distributed systems environment.
• Ability to meld the theoretical/conceptual piece of the role with the coding/production portion of the job. i.e. be able to whiteboard some theory while at the same time rolling up sleeves to immerse in hands-on coding.
• Demonstrable knowledge of core engineering fields – i.e. an understanding of how all the pieces fit together into integrated systems, and how they impact performance.
• Capability to understand research papers and being able to translate the ideas into efficient code quickly.
• Data competence and orientation – i.e. be able to set up experiments to measure things that will in turn drive decisions.
• PhD preferred.
• 5+ years of industry/academic experience
• Interest in applying machine learning & computer vision to resource constrained devices (such as mobile phones)
• Experience developing ML infrastructure
At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have a curiosity, passion and collaborative spirit, work with us, and let’s move the world forward, together
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
If you have a disability or special need that requires accommodation, please let us know by completing this form.

Apply Here

The Tech Career Guru
We will be happy to hear your thoughts

Leave a reply

Tech Jobs Here