Senior Product Manager, Experimentation Tooling

What We're Looking For

We're looking for a Founding Product Manager for Inference who will own this product end-to-end—roadmap, pricing, and GTM—from the ground up. This is a zero-to-one role at the intersection of deep technical fluency and commercial instinct. You'll define what we build and why, design the developer journey from first API call to production workload, and be the product voice in sales cycles and the market.

The right candidate has lived inside the machine; they've operated model serving infrastructure or shipped products on top of it, and can move fluidly between a latency/throughput tradeoff conversation with an infra engineer and a positioning conversation with a sales lead. You will be joining the Product Team and report to our VP of Product working directly with our executive team as we grow this business. 

This is a hybrid role based in our New York City or San Francisco office with in-office requirements of 2 days per week. 

What You’ll Do

• Own the product vision and roadmap for experimentation and developer tooling—what we build, what we don’t, and in what order
• Build the workflow layer that replaces how ML engineers and researchers manage experimentation, fine-tuning, and RL-based training today
• Own model evaluation as a product function—write evals, assess outputs, and translate quality into roadmap decisions
• Own pricing and packaging: design the consumption model, run experiments with Growth and Finance, and define tiers that convert self-serve into enterprise contracts
• Be the product voice in GTM—sales positioning, technical objection handling, and developer-facing content that builds credibility with ML engineers and platform teams
• Remove friction across the developer journey: onboarding, docs, SDK ergonomics, and observability
• Define and instrument the metrics that matter—and report them weekly to the executive team

What You’ll Need

• 7+ years of PM experience, with at least 3 in infrastructure, platform, or developer tooling
• Hands-on experience building tools for ML practitioners—you know how experiments are tracked, models evaluated, and fine-tuning jobs managed
• Experience writing or working closely with model evals; output quality directly informs your product decisions
• Owned pricing and packaging—not just features; you’ve modeled unit economics and made calls that moved margin
• Strong written and verbal communication; equally fluent in a technical spec and a customer-facing brief
• High bias for action; comfortable with ambiguity and a fast-moving environment
• BS in Computer Science, Engineering, or equivalent practical experience
• Bonus: Neocloud, hyperscaler ML platform, or AI infra startup background; PyTorch/Lightning familiarity; distributed training or fine-tuning workflow experience

Compensation