At Scale, our mission is to accelerate the development of AI applications. We are looking for a Machine Learning Research Engineer to join our Enterprise ML Research Lab, where you will 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.
As a Machine Learning Research Engineer, 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, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.
XML job scraping automation by YubHub