Machine Learning Engineer

The Role

Raydar is recruiting for this role on behalf of our client. Take ownership of machine learning work from initial scoping through to production delivery. The role combines model adaptation, measurement design and large-scale data engineering, with frequent collaboration alongside external stakeholders and internal teams.

What You'll Do

• Take responsibility for the quality of models that address customer-facing visual and multimodal problems.
• Adapt pretrained vision-language and other foundation models to specialized use cases.
• Build automated review and quality assurance workflows that draw on both commercial and open-source models.
• Develop systems that select, rank, search and annotate very large collections of data accurately.
• Design datasets, benchmarks and measurement frameworks that steadily lift model performance.
• Deliver production workflows that cover data preparation, model serving, result refinement and validation.
• Partner with stakeholders to convert loosely defined needs into systems that scale.

What We're Looking For

• At least 2 years of Python engineering experience delivering machine learning systems in production.
• Practical background with deep learning frameworks such as PyTorch, including model training and deployment.
• Sound instincts for measuring model output, judging data quality and handling unusual cases.
• Comfort driving a project from the initial problem statement through to a deployed solution.
• Clear communicator who works well with external partners and colleagues across functions.
• Ability to work on-site 5 days per week.

Bonus Points

• Exposure to video or other multimodal AI work.
• Habit of quickly experimenting with emerging AI tools and interfaces.
• Familiarity with curating or cleaning data at large scale.
• Prior time at an AI research organization or a team running high-volume ML infrastructure.

Benefits

• Health insurance

Location and Work Model

• San Francisco, CA, United States
• On-site, 5 days per week in office
• Full-time