We believe every ML team deserves world-class infrastructure — not just the ones with billion-dollar budgets.
GradientPond was founded in 2021 with a simple observation: the best ML teams in the world spend more time on infrastructure than on actual research. We set out to change that.
Our platform handles the complexity of experiment tracking, distributed training, and model deployment — so researchers and engineers can focus on what they do best: building great models.
Today, over 50,000 ML engineers at companies ranging from early-stage startups to Fortune 500 enterprises trust GradientPond to power their ML workflows.
We build tools that researchers actually want to use. Every feature starts with understanding the real workflow challenges ML teams face daily.
In ML, iteration speed is everything. We obsess over performance — from sub-millisecond logging to instant experiment comparisons.
We believe in open standards and interoperability. Our SDK is open-source, our APIs are well-documented, and we never lock you in.
Our roadmap is shaped by our community. We listen, iterate, and ship based on real feedback from the ML engineers who use our platform daily.
Your models and data are your competitive advantage. We're SOC 2 certified, GDPR compliant, and treat security as a first-class concern.
We're building infrastructure that enables breakthroughs in healthcare, climate science, and education. Great tools amplify great research.
A diverse team of ML researchers, infrastructure engineers, and product builders.
Co-Founder & CEO
Former ML infrastructure lead at Google Brain. PhD in distributed systems from MIT.
Co-Founder & CTO
Previously built distributed training systems at Meta AI. Stanford CS PhD.
VP of Engineering
10+ years building developer tools. Former engineering director at Databricks.
Head of Product
Product leader with deep ML domain expertise. Previously at Weights & Biases and Notion.
Head of Research
Published 30+ papers on distributed ML. Former research scientist at DeepMind.
VP of Sales
Enterprise sales leader. Previously scaled revenue at Snowflake and HashiCorp.
We're backed by leading venture firms and AI-focused investors.
We're hiring across engineering, research, and go-to-market. Come build the future of ML infrastructure.