ML Engineer — Vision & Multimodal in Production

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

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.