Machine Learning Engineer, Physical AI

Requirements

• About us At Encord, we're building the AI infrastructure of the future.
• The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality.
• In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market.
• As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building AI.
• AI today is what the early days of computing or the internet were like, where the potential of the technology is clear, but the tools and processes surrounding it are still primitive, preventing the next generation of applications.
• We are a talented and ambitious team of 90+, working at the cutting edge of computer vision and deep learning, backed by top investors, including CRV and Y Combinator, leading industry executives like Luc Vincent, former VP of AI at Meta, and other top Bay Area leaders in AI.
• We have big plans ahead and are looking for a Machine Learning Engineer to join us our ML team.
• You will: Experiment with and adapt latest ML technologies to fit into existing tech stack Solve idiosyncratic statistical, geometric, and engineering problems Work closely with a full stack tech team to assist implementation of research solutions into the product Contribute to hiring additional talent to our rapidly growing team The role will be exposed to a broad tech stack (e.g.
• ReactJS, Python, REST & GraphQL, OpenCV, PyTorch, GCP, AWS & CUDA, Kubernetes) and the cutting edge of computer vision and deep learning.
• Qualifications The right candidate will have a proven track record of relevant publications and previous
• experience managing applied research teams.
• Requirements for the role include: Passion for solving ML problems Strong
• experience in Python and machine learning libraries such as OpenCV, PyTorch, TensorFlow, Fast.ai , and Keras Strong
• You will get to explore and build services enterprise AI use cases across many different industry verticals such as healthcare, surveillance, retail, agriculture, and many more.
• We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.