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Scale AI

Senior/Staff Machine Learning Research Engineer, General Agents, Enterprise GenAI

Scale AI · San Francisco, CA; New York, NY

Posted about 2 months ago

or apply directly on Scale AI's site. We never take the application ourselves.

Is this posting real?

This role has been open
55 days
Scale AI's roles stay open a median of 55 days
Reposted
No
Salary listed
No
2% of Scale AI's roles list one
Ghost-job risk at Scale AI
high
183 stale, 5 reposted of 217 open
Hiring momentum
270 roles opened in the last 90 days
↑ up vs. the prior 90 days
Last confirmed on the employer's board
2026-09-27

Measured from postings appearing on and disappearing from Scale AI's own greenhouse board since 2026-08-03. Full hiring picture for Scale AI.

About this role

As a Senior/Staff Machine Learning Research Engineer on the General Agents team, you will design, build, and deploy AI agents that address significant enterprise challenges. Your role will encompass the entire agent lifecycle, from system design to deployment and iteration, ensuring that the agents are scalable and reliable for various customer environments. You will collaborate with cross-functional teams to translate enterprise needs into effective agent solutions while contributing to the technical direction of agent development.

Our read on this posting2.8out of 5
benefits
3/5
freshness
1/5
career value
5/5
role clarity
5/5
pay transparency
0/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Scale AI as an employer.

What you need

  • 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.
  • Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
  • 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.

Nice to have

  • 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.
  • Experience deploying ML systems in cloud environments and operating them at scale.
  • Experience fine-tuning or adapting foundation models using methods like supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and low-rank adaptation (LoRA) to improve agent performance on domain-specific tasks.

What you get

  • Comprehensive health, dental and vision coverage
  • Retirement benefits
  • Learning and development stipend
  • Generous PTO
  • Potential commuter stipend
  • Equity-based compensation subject to Board of Director approval.

Worth weighing

  • No specific mention of the technology stack beyond LLMs and AI agents.
  • The role may involve operating in ambiguous problem spaces, which could be challenging for some candidates.
  • Salary range provided but may vary based on multiple factors, including location and experience.
  • 90-day waiting period for reconsideration of candidates for the same role may limit opportunities for quick reapplication.

Summarised from Scale AI's posting. Read the full original.

Listed by Scale AI on their greenhouse job board, last confirmed open on 2026-09-27. PitchMeAI is not the employer.

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