Research Engineer - Reinforcement Learning
About The Position
Prime Intellect is building the open superintelligence stack, providing infrastructure that AI labs typically build internally, making it accessible to all ambitious AI teams. Their platform, Lab, integrates compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into a comprehensive full-stack system for post-training at frontier scale. This includes SFT, RL, tool use, agent workflows, and continuously improving production models. The company is focused on building open frontier AI, including open-source models trained for long-horizon tasks like autonomous research, and the platform their research team uses to develop them. Prime Intellect aims to provide AI companies, enterprises, and research teams with the ability to transform their workflows, tools, data, and feedback loops into owned superintelligence, going beyond just access to more GPUs. The company has raised $150M in funding from prominent investors and individuals in the AI and infrastructure space. They are seeking individuals passionate about building at the intersection of frontier research, real infrastructure, and go-to-market strategies for a nascent category.
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.
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.
Benefits
- Cash Compensation Range of $150-350k, including equity incentives
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
