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Machine Learning Engineer

Osmosis
🇺🇸 United States
On-site
6 days ago
$180,000 – $250,000
  • AI
  • Python
  • FastAPI
  • Golang
  • React.js
  • TypeScript
  • Next.js
  • Fargate
  • Docker
  • Kubernetes
  • AWS SageMaker
  • PyTorch
  • DynamoDB
  • Language Models
  • Vercel
  • vLLM
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About Osmosis

Reinforcement Learning (RL) for AI Agents

Tech

Backend: Python FastAPI, Golang Frontend: React, TypeScript, Next.js Cloud infrastructure: AWS Fargate, Docker, Kubernetes, AWS SageMaker ML frameworks: Verl (nice to have), PyTorch Databases: DynamoDB, S3, LanceDB

The role

### **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

Skills

  • Reinforcement learning (RL)

Machine Learning Engineer · Osmosis

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