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Technology

Machine Learning Engineer

Raydar

Workable
Location
San Mateo, California, United States, United States
Type
Full-time
Salary
Salary not specified
Posted
15 Oct 2026
About the company Our client is a software company. The role Raydar is recruiting for this role on behalf of our client. Develop and deploy bespoke machine learning models for a software product, owning the work from raw data preparation through to live operation. Collaborate with colleagues across functions to turn product ideas into shipped features, within a small, fast-moving, fully on-site team. What you'll do - Create, fit and assess proprietary neural models and learned representations that power the product. - Take charge of the full data workflow, from sourcing and cleaning through to the model fitting framework. - Strengthen the tooling used to run experiments, track results and reproduce outcomes. - Move models from early prototype into live use, then watch their behavior and refine them based on real usage. - Work with product and other colleagues to convert needs into machine learning solutions and release new capabilities. - Write tidy, efficient Python and join in peer review, testing and troubleshooting. - Follow current research developments and introduce promising techniques to the team. Requirements What we're looking for - Around 4 or more years working as a mac
About the company Our client is a software company. The role Raydar is recruiting for this role on behalf of our client. Develop and deploy bespoke machine learning models for a software product, owning the work from raw data preparation through to live operation. Collaborate with colleagues across functions to turn product ideas into shipped features, within a small, fast-moving, fully on-site team. What you'll do - Create, fit and assess proprietary neural models and learned representations that power the product. - Take charge of the full data workflow, from sourcing and cleaning through to the model fitting framework. - Strengthen the tooling used to run experiments, track results and reproduce outcomes. - Move models from early prototype into live use, then watch their behavior and refine them based on real usage. - Work with product and other colleagues to convert needs into machine learning solutions and release new capabilities. - Write tidy, efficient Python and join in peer review, testing and troubleshooting. - Follow current research developments and introduce promising techniques to the team. Requirements What we're looking for - Around 4 or more years working as a machine learning engineer in industry, or comparable research experience. - A graduate degree in a quantitative field such as computer science, with solid grounding in machine learning. - A track record of designing neural networks from the ground up rather than only adapting pretrained ones. - Experience devising original modeling approaches instead of leaning on ready-made tools. - Working knowledge of PyTorch or a similar deep learning library. - Hands-on experience with large language models and transformer architectures. - Exposure to graph-based neural architectures. - Experience delivering machine learning in production settings, with a clear sense of production standards; this is not a purely academic role. - Advanced Python skills and the ability to produce dependable code on your own. - Comfort juggling several priorities in a fast-paced startup. - Sharp problem-solving, careful attention to detail, and strong communication and collaboration. Bonus points - Familiarity with world models. - Prior work in scientific or physical-world areas such as robotics or simulation. - Experience with managed machine learning services or large cloud providers. - Backend development experience with a Python web framework and SQL. - Background in CAD or geometry-focused computing. Benefits Compensation and benefits - Base salary: USD 175,000 to 250,000 per year - Equity - Health, dental and vision coverage - Flexible time off - Professional development opportunities Location and work model - San Mateo, CA, United States - On-site, 5 days per week in the office - Full-time