Machine Learning Engineer

raydar; California; On-site; USD 150,000 - 350,000; Full time

Benefits offered by this job

Health insurance

Job summary

Raydar in San Francisco is seeking an experienced machine learning engineer to own end-to-end ML work from scoping to production delivery. You will adapt vision-language models, design measurement frameworks, and build data pipelines for large-scale datasets.

The role emphasizes collaboration with external partners and internal teams, ensuring model quality and scalable solutions. On-site, full-time with competitive compensation and health insurance.

Qualifications

• 2+ years of Python engineering experience delivering machine learning systems in production.
• Hands-on experience with PyTorch for model training and deployment.
• Ability to measure model outputs and assess data quality.
• Experience driving a project from problem statement to deployed solution.
• Strong communication skills with external partners and cross-functional teams.

Responsibilities

• Take ownership of model quality for customer-facing visual and multimodal problems.
• Adapt pretrained vision-language and other foundation models to specialized use cases.
• Build automated review and QA workflows using both commercial and open-source models.
• Develop systems that index, search, and annotate large data collections accurately.
• Design datasets, benchmarks, and measurement frameworks to lift model performance.
• Deliver production workflows for data prep, model serving, and result validation.
• Collaborate with stakeholders to translate needs into scalable systems.

Skills

Python

PyTorch

ML deployment

Data quality

Stakeholder communication

Job description

About the company

Our client is a fast-growing technology company.

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.

Requirements

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

Compensation and benefits

• Base salary: USD 150,000 to 350,000 per year

• Health insurance

Location and work model

• San Francisco, CA, United States

• On-site, 5 days per week in office

• Full-time