Research Engineer - Reinforcement Learning

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 https://a.co/d/frW8MHY, here https://a.co/d/4WRhR0Y and here https://github.com/stas00/ml-engineering/tree/master) 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. 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.