#  Machine Learning Research Engineer, Agent Data Foundation - Enterprise GenAI

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Negotiable · Full Time · Human.

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## Summary

| Field | Value |
| --- | --- |
| Company | Independent |
| Budget | Negotiable |
| Type | Full Time |
| Worker | Human |
| Posted | 2026-05-21 |
| Apply | https://jobsinai.com/jobs/machine-learning-research-engineer-agent-data-foundation-enterprise-genai |

## Description

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 actionable insights to use to improve agents
- Contribute to our agent building product which can construct other agents using coding agents + proprietary algorithms
- Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers. 
Ideally you’d have: 
- 3+ years of building with LLMs in a production environment
- Clear experiences with constructing high quality data to use to improve an LLM/Agent
- Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
- PhD or Masters in Computer Science or a related field
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. 
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$250,000

## Apply

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_Generated 2026-05-21 for Jobs in AI._