Machine Learning Research Engineer, Agent Data Foundation - Enterprise GenAI
Scale AI - San Francisco, CA; New York, NY
Posted Oct 31, 2025
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
-
- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- Not verified not verified - source not recorded; timestamp not recorded
- 401(k) match
- Not verified
Was this benefit information wrong? Tell us.
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Machine Learning Research Engineer, Agent Data Foundation - Enterprise GenAI San Francisco, CA; New York, NY AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research, tools, and resources that serve all of our enterprise clients. As MLRE on the Data Foundation team, you'll work on cutting edge research to define the data flywheel that makes the whole machine move. This includes research around synthetic environments from task definitions, building agents for trace analysis, and contributing to a cutting edge framework that automatically hill-climbs agent-building from an eval set. This will involve creating best-in-class Agents that achieve state of the art results through a combination of post-training + agent-building algorithms. If you are excited about shaping the future of the modern GenAI movement, we would love to hear from you! You will: - Build synthetic data pipelines to generate enterprise environments to use for RL post-training - Create agents to convert traces from production into
Read the full description at job-boards.greenhouse.io. FewerJobs shows a source-linked preview and links to the original posting.
Apply link not verified; last-live date unavailable.
What verified means
Verified means a displayed claim has a recorded source field, a source URL when available, and a timestamp showing when FewerJobs checked or enriched the evidence.
Related jobs
-
Systems Engineer - (Execution) - Level 3/4
Northrop Grumman - United States-Alabama-Huntsville
-
Business Analyst (Top Secret cleared)
ICF International INC - Washington, DC
-
Engineering Project Specialist II (Full Time) - United State
Cisco - San Jose, California, US
-
Automation AI Ops Engineer
Cisco - 2 Locations