Member of Technical Staff, Forward Deployed
Chakra Labs · New York
About this role
## About Chakra Labs Chakra Labs’ mission is to encode human taste into intelligence. We build high-fidelity environments, evals, and datasets for frontier AI research—working with top labs. Our work focuses on post-training, agent environments, data quality, and research infrastructure. We care about building systems that make models better in ways that are **measurable, useful, and hard to fake**. --- ## What You’d Work On - **The hardest problems at the frontier**: a new environment modality, an eval targeting an unmeasured failure mode, or a dataset that doesn’t exist yet. - **Environments, evals, and datasets**: one project might be a high-fidelity environment, the next a task distribution with grading logic, and the next a dataset built to a demanding spec. - **Pulling the frontier into the platform**: when a custom build proves out a capability worth generalizing, you help fold it into the core product so it compounds. - **Own the deliverable**: you’ll write whatever the work needs—environment code, task specs, and scoring harnesses. --- ## About You - **Full-stack range**: strong generalist engineering across backend services, data pipelines, and enough frontend to ship a usable interface. TypeScript/Python (or similar). - **Fast in ambiguity**: requirements often arrive as a hunch, not a spec. You can turn a loosely-defined research question into a concrete environment, task set, eval, or dataset—and validate it measures what was intended. - **Customer instincts**: clear communication with researchers and technical customers, plus the ability to push back when something requested isn’t what’s needed. Work spans deep async stretches and high-bandwidth customer sessions. - **Evals curiosity**: you don’t need an ML research background, but you’re genuinely interested in how agents fail and how to measure it. You’ll learn task design, LLM-judged scoring, and reward hacking detection. - **Experience**: ideally 3+ years shipping production software (but less can work if you match the above). --- ## What Makes This Different - **You see the frontier first**: problems you tackle are often ones frontier researchers haven’t solved yet. - **Real customers, real deadlines**: every project has a named customer and a researcher waiting on the output. - **Ownership, not theater**: you own whole deliverables and customer relationships—not tickets. - **A strong team**: ex-Stripe, Snap, AWS, Microsoft, Airtable. - **Cutting edge**: you’ll work across the latest technologies across data, AI, and infrastructure.
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