Applied Research - RL & Agents

Prime Intellect
San Francisco
Workplace: OnsiteFull timeFunction: Research & Scientific (R&D)Skills: ["Communication","Collaboration","Problem-solving","Writing"]

We seek a machine learning engineer focused on reinforcement learning and applied agent systems to design next-generation AI agents, build scalable inference/training infrastructure, and bridge research with real-world deployments. You’ll prototype agents, eval harnesses, and environment tooling, collaborate with researchers and infra teams, and contribute to production-ready RL/post-training solutions at frontier scale.

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FursaFursa
Prime Intellect
Prime Intellect
11 months ago

Applied Research - RL & Agents

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Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

We seek a machine learning engineer focused on reinforcement learning and applied agent systems to design next-generation AI agents, build scalable inference/training infrastructure, and bridge research with real-world deployments. You’ll prototype agents, eval harnesses, and environment tooling, collaborate with researchers and infra teams, and contribute to production-ready RL/post-training solutions at frontier scale.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •Design and implement new RL and post-training methods and agent architectures to tackle real workloads.
  • •Build and maintain robust agent infrastructure, including training and inference pipelines, to operate at scale.
  • •Translate ambiguous objectives into concrete technical requirements to guide product and research priorities.
  • •Prototype agents, eval harnesses, and environments tailored to real-world use cases and external systems.
  • •Collaborate with researchers, infra teams, and external partners to reflect real workloads in the stack.

Pay and Benefits

Perks:Learning BudgetRemote Work

Key Requirements

  • •Strong background in machine learning engineering with experience in post-training, RL, or large-scale model alignment.
  • •Experience with agent frameworks and tooling (e.g. DSPy, LangGraph, MCP, Stagehand).
  • •Familiarity with distributed training/inference frameworks (e.g., vLLM, sglang, Accelerate, Ray, Torch).
  • •Track record of research contributions (publications, open-source contributions, benchmarks) in ML/RL.
  • •Strong technical writing abilities (documentation, blogs, papers) and research taste.
Experience:AIMachine learningRLOpen source
Skills:CommunicationCollaborationProblem-solvingWriting
Tech Stack:DSPyLangGraphMCPStagehandVLLMSglangAccelerateRayTorchPrometheusGrafanaDockerKubernetes

Company Brief

Prime Intellect
Builds a decentralized, open compute and training platform that enables distributed training and collective ownership of AI models, aggregating global GPU resources and offering tools for agentic RL and model evaluation.
Industry: AI & Machine Learning
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Funding: Seed
Headquarters: San Francisco, United States
Founded: 2024
WebsiteLinkedIn