Founding Member of Technical Staff
About the Role
This is a founding engineering role at an early-stage healthtech / safety-critical AI startup building evidence infrastructure for AI model validation in medical diagnostics. As a Founding Member of Technical Staff, you will help shape the core reasoning methodology that underpins how AI safety claims are investigated, structured, and validated — across the full product lifecycle. You'll work directly alongside the founding team, contributing across technical domains and helping lay the infrastructure for the future of safety-critical AI.
What You'll Do
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Design and execute investigations into how AI models perform and fail across real-world scenarios.
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Analyze input data, model outputs, and internal representations to evaluate data quality, generalization limits, distribution shift, subgroup performance, and demographic bias.
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Surface failure modes and produce structured evidence that supports, challenges, or refines claims about model performance and safety.
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Develop and evolve the company's evidence methodology — defining how claims, arguments, and evidence should be structured for rigorous AI validation.
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Pressure-test assumptions, critique weak argument structures, and systematize repeated investigations into reusable methods, workflows, and platform primitives.
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Write production-quality Python, build agentic workflows for evidence investigation, and prototype front-end features using AI tooling.
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Contribute beyond your immediate technical domain — this is a founding role that requires ownership, versatility, and the willingness to challenge assumptions.
What We're Looking For
Required:
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Degree in CS, mathematics, physics, engineering, or a related quantitative field — or equivalent demonstrated depth.
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Strong ML, statistics, and data science fundamentals; ability to understand the math behind methods, identify broken assumptions, and reason about trade-offs.
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Expert Python skills, spanning raw data analysis through to platform-level code others will rely on.
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Strong engineering judgment on code structure, interface boundaries, and reusability trade-offs.
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Demonstrated ability to operate as a founding-team-caliber contributor — taking end-to-end ownership and contributing across domains.
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Strong cross-functional communication skills; able to present evidence, claims, and validation results to both technical and non-technical stakeholders.
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Comfort using AI tooling as a primary mode of working.
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Authorized to work in the United States without visa sponsorship; able to work on-site in Sunnyvale, CA.
Nice to Have:
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3–5 years of professional ML experience, or a PhD in model evaluation, robustness, out-of-distribution detection, interpretability, or a related area.
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Experience with AI/ML medical device submissions, FDA review processes, or other regulated environments (e.g., FDA 510(k), De Novo, EU AI Act).
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Background in safety case methodology in aviation, automotive, healthcare, or other safety-critical fields.
Compensation & Benefits
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Salary: $150,000 – $200,000 USD annually
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Founding team equity and early-stage upside
Location
On-site in Sunnyvale, CA, United States . This is a full-time, in-office role. Visa sponsorship is not available — candidates must be authorized to work in the US without sponsorship.
Originally posted on Himalayas