Research Engineer - Reinforcement Learning

Prime Intellect, Inc.; United States; Hybrid; USD 150,000 - 350,000; Full time

Benefits offered by this job

Visa sponsorship

Relocation assistance

Quarterly team off-sites

Hackathons

Learning opportunities

Job summary

Prime Intellect, Inc. is building the open frontier AI stack and a massive-scale synthetic data generation platform. You will contribute to end-to-end pipelines for training and inference of large-scale models, focusing on distributed inference and memory optimization.

The role emphasizes publishing, open-source work, and advancing AI tooling for researchers and enterprises. You’ll join a mission-driven team in San Francisco with flexible remote options and opportunities for global impact across

Qualifications

• End-to-end pipelines for inference or training of large-scale AI models.
• Distributed inference techniques and frameworks (e.g. vllm, sglang) to optimize performance and scalability.
• MLOps best practices: model versioning, experiment tracking, CI/CD pipelines.
• Passion for advancing AI state-of-the-art and democratizing access to capabilities.

Responsibilities

• Lead and participate in novel research for massive-scale synthetic data generation and orchestration.
• Optimize AI inference workloads for performance and cost using the latest compute/memory techniques.
• Contribute to open-source libraries and RL frameworks for synthetic data generation.
• Publish research in ICML and NeurIPS.
• Distill project outcomes in layman blogs for customers and developers.
• Stay up-to-date with AI/ML infra advancements and identify opportunities to enhance our platform.

Skills

AI/ML engineering

Distributed inference

MLOps

Research publication

Tools

vllm

sglang

Job description

Own Your Intelligence

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full‑stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.

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.