Research Engineer - Reinforcement Learning

Prime Intellect
San Francisco, United States
Workplace: OnsiteFull timeFunction: Education & TrainingSkills: ["Communication","Problem-solving","Collaboration"]

Research Engineer in the Reasoning team focusing on test-time compute scaling for reinforcement learning at frontier scale. You’ll lead and participate in novel research to build massive-scale synthetic data pipelines, optimize AI inference workloads, contribute to open-source libraries, publish at top AI conferences, and distill complex results for customers and developers.

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FursaFursa
Prime Intellect
Prime Intellect
2 years ago

Research Engineer - Reinforcement Learning

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

Job Summary

Research Engineer in the Reasoning team focusing on test-time compute scaling for reinforcement learning at frontier scale. You’ll lead and participate in novel research to build massive-scale synthetic data pipelines, optimize AI inference workloads, contribute to open-source libraries, publish at top AI conferences, and distill complex results for customers and developers.
Location: San Francisco, United States
Workplace: Onsite
Employment Type: Full time
Job Function: Education & Training

Key Responsibilities

  • •Lead and participate in novel research to build a massive scale synthetic data generation pipeline and orchestration solution.
  • •Optimize the performance, cost, and resource utilization of AI inference workloads by leveraging the most recent advances for compute & memory optimization techniques.
  • •Contribute to the development of our open-source libraries and frameworks for synthetic data generation and distributed RL frameworks.
  • •Publish research in top-tier AI conferences such as ICML & NeurIPS.
  • •Distill highly technical project outcomes in layman approachable technical blogs to our customers and developers.

Pay and Benefits

Equity and Bonus:Equity
Perks:Remote WorkEquity

Key Requirements

  • •Strong background in AI/ML engineering with end-to-end pipelines for inference or training of large-scale AI models.
  • •Deep expertise in distributed inference techniques and frameworks (e.g. vllm, sglang) for optimizing performance and scalability of AI workloads.
  • •Solid understanding of MLOps best practices, including model versioning, experiment tracking, and CI/CD pipelines.
  • •Passion for advancing the state-of-the-art in reasoning and democratizing access to AI capabilities for researchers, developers, and businesses worldwide.
  • •Familiarity with the resources linked in the description and willingness to engage with the project community.
Experience:AI/ML
Skills:CommunicationProblem-solvingCollaboration
Tech Stack:VllmSglangMLOpsCI/CDDistributed inferenceReinforcement learning

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