Research Engineer - Reinforcement Learning

Prime Intellect

$150K — $350K *
US-AnywhereRemote in San Francisco, CA
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong background in AI/ML engineering and large-scale model pipelines.
  • Deep expertise in distributed inference frameworks for performance optimization.
  • Solid understanding of MLOps practices like model versioning and CI/CD.
  • Passionate about democratizing AI capabilities for diverse users.
  • Willingness to learn and engage with new technologies relevant to our mission.

Responsibilities

  • Lead research to develop a large-scale synthetic data generation pipeline.
  • Optimize AI inference workloads using advanced compute and memory techniques.
  • Contribute to open-source libraries for synthetic data generation and distributed RL.
  • Publish findings in top-tier AI conferences such as ICML and NeurIPS.
  • Create accessible technical blogs from complex research outcomes.
  • Stay updated on AI/ML infrastructure advancements to enhance platform capabilities.

Benefits

  • Flexible work arrangements, with remote or in-person options.
  • Visa sponsorship and relocation assistance for international applicants.
  • Quarterly team events like off-sites and hackathons.
  • Learning opportunities through conferences and skill development.
  • Work in a mission-driven team focused on leveraging technology for science and AI.
Full Job Description
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.
  • Stay up-to-date with the latest advancements in AI/ML infrastructure and tools, synthetic data gen research and proactively identify opportunities to enhance our platform's capabilities and user experience.
Requirements
  • Strong background in AI/ML engineering, with extensive experience in designing and implementing end-to-end pipelines for the inference or training of large-scale AI models.
  • Deep expertise in distributed inference techniques and frameworks (e.g. vllm, sglang) for optimizing the performance and scalability of AI workloads.
  • Solid understanding of MLOps best practices, including model versioning, experiment tracking, and continuous integration/deployment (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.
  • If you're not familiar with these, but feel like that you can contribute to our mission and you're a high-energy person, get familiar with these resources (here, here and here) and please reach out!
Benefits & Perks
  • Cash Compensation Range of $150-350k, including equity incentives, aligning your success with the growth and impact of Prime Intellect.
  • Flexible work arrangements, with the option to work remotely or in-person at our offices in San Francisco.
  • Visa sponsorship and relocation assistance for international candidates.
  • Quarterly team off-sites, hackathons, conferences and learning opportunities.
  • Opportunity to work with a talented, hard-working and mission-driven team, united by a shared passion for leveraging technology to accelerate science and AI.

We recently raised $15mm in funding (total of $20mm raised) led by Founders Fund, with participation from Menlo Ventures and prominent angels including Andrej Karpathy (Eureka AI, Tesla, OpenAI), Tri Dao (Chief Scientific Officer of Together AI), Dylan Patel (SemiAnalysis), Clem Delangue (Huggingface), Emad Mostaque (Stability AI) and many others.

If you're excited about the opportunity to build the foundation for the future of decentralized AI and create a platform that empowers developers and researchers to push the boundaries of what's possible, we'd love to hear from you.

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