- B2B
- Early StageStartup in initial stages
Stochastic careers
Most AI systems are built as one-size-fits-all solutions. Powerful in benchmarks, brittle in production. In a real workplace, they fall short. Not because they lack intelligence, but because they don't know your business. They're missing your domain knowledge, your workflows, your team's preferences, and the unwritten rules that make your organization run. That gap between general intelligence and operational context is where most enterprise AI implementations fail.
Stochastic was built to close that gap. We give enterprises a private, tailored AI system they fully own. One that learns continuously from real behavior and user feedback, adapts to their specific environment, and gets sharper the longer it's in use. Because the system is theirs, so is the data. No shared model training, no compromised proprietary information. Just an AI that knows your organization as well as your best employee does, and keeps getting better.
Stochastic started with a group of Harvard AI systems researchers who built the first Bayesian and LLM inference accelerators, along with a real-time speech and NLP engine. The team has since grown to include engineers and researchers from Stanford, CMU, MIT, UIUC, NVIDIA, and Meta, all building toward the same goal: AI that belongs to your organization, not to anyone else.
Stochastic was built to close that gap. We give enterprises a private, tailored AI system they fully own. One that learns continuously from real behavior and user feedback, adapts to their specific environment, and gets sharper the longer it's in use. Because the system is theirs, so is the data. No shared model training, no compromised proprietary information. Just an AI that knows your organization as well as your best employee does, and keeps getting better.
Stochastic started with a group of Harvard AI systems researchers who built the first Bayesian and LLM inference accelerators, along with a real-time speech and NLP engine. The team has since grown to include engineers and researchers from Stanford, CMU, MIT, UIUC, NVIDIA, and Meta, all building toward the same goal: AI that belongs to your organization, not to anyone else.
AI Engineer
In office • New York City • San Francisco
$150k – $230k • 0.0% – 0.5%2 weeks ago
Full-Stack Engineer
In office • New York City • San Francisco
$60k – $140k • 0.0% – 0.5%2 weeks ago
Jatin Sarda
A full stack developer with 5+ years of production experience and a passion for creating intuitive user interfaces.
Proficient in React, Typescript, Python
Aishwarya B S
AI ML Engineer with hands-on experience in Machine Learning, Deep Learning and Agentic AI. Skilled in Python, TensorFlow, Autogen, NextJS, Flask and Docker.
Yasha Bajaj
