Senior/Staff Machine Learning Research Engineer, General Agents, Enterprise GenAI
Scale AI · San Francisco, CA; New York, NY · Applications Platform Engineering · listed February 10, 2026
The shape of it
Seniority
Staff
Experience asked
5+ years
Where
Not stated
Stated pay
$264,800 – $331,000 USD
Requirements listed
8
Length
1,007 words
In the posting’s own words
As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.
What it asks for · 8
- 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
- Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
- Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
- Experience building systems that integrate models with external tools, APIs, databases, and services.
- Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
- Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs).
- Experience with agent frameworks, orchestration layers, or workflow systems (e.g., tool calling, planners, multi-agent setups).
- Familiarity with evaluation, monitoring, and observability for LLM-powered systems in production.
Degree language
- Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
Tools and skills named
Models & research
- LLM4×
- Machine learning4×
- Fine-tuning2×
- Reinforcement learning
Cloud & infra
- Observability
Languages
- Python
Ways of working
- Cross-functional
Words the posting leans on
- agent14×
- systems10×
- experience7×
- enterprise6×
- data4×
- design4×
- production4×
- tool4×
- constraints3×
- customers3×
- deploying3×
- evaluation3×
- experience building3×
- llms3×
- machine learning3×
- models3×
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