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Founding Member of Technical Staff — Product / Full-Stack Engineering

TensorZero
New York City, United Statesfull_timeVerifiedPosted 29 Apr 2025
💰 $300,000/yr($200,000/yr$300,000/yr)

About the role

TensorZero is an open-source platform that creates a feedback loop for optimizing LLM applications — turning production data into smarter, faster, and cheaper models.

  1. Integrate our model gateway

  2. Send metrics or feedback

  3. Optimize prompts, models, and inference strategies

  4. Watch your LLMs improve over time

It enables a data & learning flywheel for LLMs by unifying:

  • Inference: one API for all LLMs, with <1ms P99 overhead

  • Observability: inference & feedback → your database

  • Optimization: from prompts to fine-tuning and RL

  • Evaluations: compare prompts, models, inference strategies

  • Experimentation: built-in A/B testing, routing, fallbacks

We’ve raised from FirstMark (backed ClickHouse), Bessemer (backed Anthropic), Bedrock (backed OpenAI), and many angels. We’re lucky to have years of runway, giving us the flexibility to fully focus on open source for now with an ambitious long-term vision.

Role

We are looking for a Founding Member of Technical Staff who's hungry to learn and contribute across the stack. Early on, you'll work as a product engineer focused on the highest-impact user-facing features.

You'll work alongside and learn from experts in front-end (e.g. co-creator of Radix UI, React Router, RemixJS), back-end (e.g. ex-maintainer of the Rust compiler), and ML (e.g. researchers with thousands of citations).

The vast majority of your work will be open source. You can learn more about our technical roadmap and vision here.

Team & Culture

We’re a small technical team based in NYC (in person). As an early contributor, you’ll work closely with us and have a significant impact on the project’s future and vision.

  • Viraj Mehta (CTO) recently completed his PhD from Carnegie Mellon, with an emphasis on reinforcement learning for LLMs and nuclear fusion, and previously worked in machine learning at KKR and a fintech startup; he holds a BS in math and an MS in computer science from Stanford.

  • Gabriel Bianconi (CEO) was the chief product officer at Ondo Finance ($10B+ valuation) and previously spent years consulting on machine learning for companies ranging from early-stage tech startups to some of the largest financial firms; he holds BS and MS degrees in computer science from Stanford.

  • Andrew Jesson (MTS) is an ML researcher with deep expertise in Bayesian ML, causal inference, RL, and LLMs. He’s finishing his post-doc at Columbia and previously received a PhD from Oxford, during which he interned at FAIR. He has 3.3k+ citations and several first-author papers at NeurIPS and other top ML venues.

  • Aaron Hill (MTS) is a back-end engineer with deep expertise in Rust. He became one of the maintainers of the Rust compiler team… while still in college. Later, he worked on back-end infrastructure at AWS and Svix. He’s also an active contributor to many notable open-source Rust projects (e.g. Ruffle).

  • _____ You?

What We Offer

  • Competitive compensation — We believe that great talent deserves great compensation (salary, equity, benefits), even at an early-stage startup.

  • Open-source contributions — The vast majority of your work will be open-source and public.

  • Learning and growth opportunities — You'll work alongside experts in front-end, back-end, and ML to build high-impact user-facing products.

  • Small, technical, in-person team — You’ll work alongside a 100% technical team and help shape our vision, culture, and engineering practices.

  • Best-in-class investors — We’re lucky to be backed by leading funds like FirstMark (backed ClickHouse), Bessemer (backed Anthropic), Bedrock (backed OpenAI), and many angels. We have years of runway and a long-term mindset.

We’re Looking For

  • Strong technical background — You’ve tackled hard technical problems. You’re comfortable driving large projects from inception to deployment (to start, TensorZero’s observability d

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Company

TensorZero

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