What Osmosis does
Osmosis is a post-training platform that helps companies fine-tune language models using reinforcement learning. We work with fast-growing AI companies to train task/domain-specific models that beat foundation models on performance, cost, and latency. Our platform handles compute orchestration, reward modeling, and training run observability as a CLI-based product usable by developers and agents.
1 open role
What the role involves
About Osmosis At Osmosis, we help companies use cutting-edge reinforcement learning techniques to fine-tune open-source language models that beat foundation models on performance, latency, and cost. We’ve raised $7M in funding from Y Combinator, top institutional investors like CRV and Audacious Ventures, as well as angel investors including Paul Graham (Y Combinator), Erik Bernhardsson (Modal Labs), Misha Laskin (Reflection AI), and Guillermo Rauch (Vercel). About the Role We're looking for a Machine Learning Engineer to contribute to high-performance distributed training infrastructure for RL at scale. You'll work directly with our founding team and design partners to push the boundaries of what's possible with post-training and continual learning systems. This role requires expertise in RL algorithms, distributed training, and low-level optimization. You'll have exceptional agency to make impactful decisions while working in a fast-paced, customer-driven environment. Responsibilities You’ll contribute to work in areas like: Distributed Training Infrastructure: implement new RL algorithms and build scalable post-training pipelines Resource Management & Optimization: design infrastructure systems for efficient GPU utilization and dynamic resource allocation Customer-Facing Work: work directly with customers on production deployments and custom model development Technology Backend: Python FastAPI, Golang Frontend: React, TypeScript, Next.js Cloud Infrastructure: AWS Fargate, Docker, Kubernetes, AWS SageMaker ML Frameworks: Verl / slime / Megatron-LM / SkyRL, PyTorch (FSDP experience is a plus), vLLM / SGLang Databases: DynamoDB, S3
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Company facts compiled from public sources and last refreshed 9 September 2026. Details change; treat the company’s own site as the authority.