Osmosis blog · Jun 2026
Describes a fused Triton logprob kernel that reduced RL training time and increased trainable context length for long-context reinforcement learning.
Company research
Public company, workplace, funding, and market signals
Updated Jul 30, 2026
Overview
San Francisco-based YC W25 startup founded in 2024 by Kasey Zhang and Baiqing Lyu, building a forward-deployed reinforcement fine-tuning platform for AI agents and task-specific models that improve from real usage.
Primary product
Forward-deployed reinforcement fine-tuning / post-training platform for AI agents
Founded
2024
Headquarters
San Francisco, California, United States
Team size
1-10
Industry
Technology, Information and Internet
Sub-industry
AI infrastructure / reinforcement learning platform for agentic AI
Offices
San Francisco, California, United States
Business model
B2B SaaS
enterprise AI platform
AI infrastructure
Funding
People & investors
Work & culture
Technical, customer-facing, and hands-on; the company emphasizes bleeding-edge work, direct support with customers, high agency, and a paid in-person work trial in hiring.
Visa sponsorship
Limited
Compensation
Public hiring signals show full-time ML roles at $180K-$250K base salary in San Francisco; no public equity or bonus details were found.
Product & market
Pricing
Not publicly disclosed; appears to be sold as a B2B platform / enterprise software offering.
Differentiators
- —Reinforcement fine-tuning for agentic AI rather than static prompt-only workflows
- —Real-time / continuous retraining from production interactions
- —Own-your-weights model export and self-host/VPC deployment
- —Direct, hands-on support through the full post-training workflow
- —Tool-use training and MCP-oriented workflows
- —Designed for task-specific models that can beat foundation models on performance, cost, and latency
Technology
Python
FastAPI
Go
React
TypeScript
Next.js
Docker
Kubernetes
AWS Fargate
AWS SageMaker
PyTorch
DynamoDB
S3
LanceDB
Triton
Megatron-LM
SGLang
GRPO
DAPO
MCP
Customers
Fast-growing AI companies
Teams building AI agents
Engineering teams training task/domain-specific models
Customers needing reliable tool use, code generation, or domain-specific extraction
Competitors
OpenPipe
Databricks Mosaic AI
Scale AI
Modal Labs
LangSmith
Weights & Biases
Scale & contact
Latest news
Osmosis blog · Jun 2026
Explains a multi-LoRA/Megatron-Bridge approach that enabled thousands of concurrent LoRA adapter trainings and improved throughput.
Signalbase · Oct 2025
Reports the company’s $6.3M seed round and says the capital will be used to scale operations, expand engineering and research, and accelerate product R&D.
Osmosis blog · Jul 2025
Introduces Osmosis-Apply-1.7B, an RL-tuned model for code merging that the company says outperformed larger foundation models on its validation benchmark.
Y Combinator
YC launch page describing Osmosis as infrastructure that lets AI agents learn from tasks in real time, with claims about accuracy, cost-efficiency, and fewer steps per task.
Jobs and careers at Osmosis
7 jobs at Osmosis
Medical Assessment and Content Editors
Remote
Content
Northeastern USA; Remote (North America); Western USA
1mo ago
Remote
Full-time
Clinical Content Editor - PGY-1/Medical Students
Remote
Medical Content
Remote (North America)
10mo ago
Remote
Full-time
Panel Review Subject Matter Expert (SME)
Remote
Medical Content
Remote (North America)
10mo ago
Remote
Full-time
Osmosis Nursing Content Creator
On-site
Nursing Content
Anywhere
11mo ago
On-site
Full-time
Elsevier Clinical Content Reviewer, Specialty Specific (Part-Time, Fixed Term Contract). International (UK, AUS, NZ) Applicants Only
On-site
Medical Content
Anywhere
1y ago
On-site
Full-time
Elsevier Clinical Content Reviewer, Specialty Specific (Part-Time, Fixed Term Contract)
Remote
Medical Content
Remote (North America)
1y ago
Remote
Full-time
General Application
On-site
Open Application
Anywhere
1y ago
On-site
Full-time