Staff ML Research Engineer - Production Agentic AI

United States Digital Space LLC; San Francisco, New York (CA, NY); On-site; USD 170,000 - 284,000; Full time

Benefits offered by this job

Health coverage

Dental coverage

Vision coverage

Retirement benefits

Learning stipend

Generous PTO

Commuter stipend

Job summary

Scale is seeking a Staff Machine Learning Research Engineer to work across the AIS team on the Scale Generative AI Platform. You will train, fine-tune, and evaluate models, build production-ready pipelines, and shape the AI/ML direction across multiple teams.

You will mentor engineers and scientists, collaborate with product and deployment groups, and push research into scalable production systems while advancing agent capabilities and reliability at scale.

Qualifications

• 5+ years of experience as an ML engineer or applied/research scientist
• PhD in Computer Science, Electrical Engineering, or related field
• Broad fluency across the agentic ML stack with demonstrated depth in at least one area
• Ability to move across problem areas and responsibilities across teams
• Experience partnering with software engineers to productionize research and push code to production

Responsibilities

• Move across AIS’s core problem areas as needed (training/fine-tuning, inference, memory and retrieval)
• Research and prototype novel methods for agent performance improvements with rigorous experiments
• Build AI agents and internal tooling to reduce bottlenecks in AIS processes
• Collaborate with ML engineers, software engineers, product managers, customers, and DE engineers to ship production systems
• Set AI/ML technical direction and mentor engineers across teams

Skills

ML engineering

Production ML

Mentoring engineers

Cross-team collaboration

Education

PhD in Computer Science or related field

Tools

Training pipelines

Evaluation systems

Job description

Scale is seeking a Staff Machine Learning Research Engineer to work across the AIS team on the Scale Generative AI Platform. You will train, fine-tune, and evaluate models, build production-ready pipelines, and shape the AI/ML direction across multiple teams.

You will mentor engineers and scientists, collaborate with product and deployment groups, and push research into scalable production systems while advancing agent capabilities and reliability at scale.