Applied Machine Learning Engineer

Requirements

• You’ve trained ML models that made it into production and helped thousands of people
• (Desirable) You’ve led self-directed R&D projects and know how to navigate and spend time effectively in new and uncertain domains
• You are excited to find ways to get 80% of the benefit from 20% of the effort, to push our understanding and our product forward at pace. You thrive in small mission-driven teams taking smart bets and learning as they go
• (Desirable) You’ve previously worked in HealthTech or have experience with biometrics or high-frequency time series data
• You invest time to understand the products you work on and their users, and are a valued voice in product discussions and ideation. You’re motivated to use your skills to help the more than 250,000 people using Visible to manage complex chronic illnesses
• You use Claude Code or Codex (or similar) regularly and know how to delegate effectively to AI agents
• You’re proactive and motivated to build a product you can be proud of: when you see how we could make something better, you make it happen
• You form views based on evidence and change them when the evidence changes, always in service of our members and our business

What the job involves

• You’ll develop production-grade machine learning models in novel and emerging domains (e.g. predicting symptom flare-ups, treatment effectiveness, diagnosis assistance using extensive time-series datasets)
• You’ll perform exploratory data analysis on both product and health data, and occasionally assist with product experiments (mostly A/B tests, some quasi-experimental)
• You’ll report to Paul, our Data Science Lead, in a small, low-ego team of 11: three engineers, one QA (we’re hiring a second), three designers, two data scientists, a behavioural scientist, and a PM. We’re ambitious about what we’re building and pragmatic about how we work
• You’ll support collaborations with researchers at top institutions (Imperial College London, Mount Sinai, Oxford, Yale) to inform robust, scientifically validated model development
• You’ll work with our flexible tech stack: GCP, BigQuery, Python, Postgres, and our time series database InfluxDB

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