Machine Learning Research Engineer, Agent Data Foundation - Enterprise GenAI

Scale AI
San Francisco, New York
Workplace: OnsiteFull timeUSD 218,400 - 273,000 annuallyFunction: Data Science & Machine LearningExperience: 3+ yearsEducation: mastersSkills: ["Communication","Problem-solving","Collaboration"]

Join Scale AI's Enterprise ML Research Lab to advance GenAI by building synthetic data pipelines, developing agents from production traces, and contributing to an agent-building framework. You’ll train state-of-the-art models for enterprise deployments, focusing on post-training and agent-building algorithms to improve enterprise-agent performance across multiple internal projects.

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FursaFursa
Scale AI
Scale AI
10 months ago

Machine Learning Research Engineer, Agent Data Foundation - Enterprise GenAI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 8 hours agoStatus: Live

Job Summary

Join Scale AI's Enterprise ML Research Lab to advance GenAI by building synthetic data pipelines, developing agents from production traces, and contributing to an agent-building framework. You’ll train state-of-the-art models for enterprise deployments, focusing on post-training and agent-building algorithms to improve enterprise-agent performance across multiple internal projects.
Location: San Francisco, New York
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •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

Pay and Benefits

Salary: USD 218,400 - 273,000 annually
Perks:Health InsuranceDentalVisionRetirement BenefitsLearning BudgetCommuter BenefitsPaid Leave

Key Requirements

  • •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
Experience:3+ yearsGenAILLMsEnterprise
Education:Master's
Skills:CommunicationProblem-solvingCollaboration
Languages:English
Tech Stack:LLMsRLSynthetic dataPython

Company Brief

Scale AI
Provides data labeling, annotation, and infrastructure services to accelerate machine learning and AI development. Supplies high-quality training data, tooling, and APIs for customers in autonomous vehicles, mapping, robotics, and enterprise AI applications.
Industry: AI & Machine Learning
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2016
WebsiteLinkedIn