Applied Machine Learning Engineer, Visible

• Passionate about applying ML and data science to chronic health conditions, driven by the goal of improving patient lives
• Experienced in building, deploying, and scaling ML models in production environments, ideally within dynamic tech environments
• Strong engineering skills, comfortable with end-to-end ML lifecycle management, including model monitoring, optimization, and maintenance
• A product-minded individual focused on customer outcomes and data-informed decision-making
• Proactive, self-directed, and willing to take on end-to-end ownership: we are a small, high-agency team, where you’ll be driving your own projects and collaborating with fantastic people

Desirable

• Developing and deploying production-grade machine learning models addressing key challenges (e.g., predicting symptom flare-ups, treatment effectiveness, diagnosis assistance) using extensive time-series datasets
• Collaborating closely with our Data Science Lead, product, design, and engineering teams to integrate ML models into the Visible app, enhancing the daily experience for tens of thousands of users
• Supporting collaborations with researchers at top institutions (Imperial College London, Mount Sinai, Oxford, Yale) to inform robust, scientifically validated model development
• Maintaining and improving infrastructure required to deploy and scale ML models efficiently, contributing to architectural decisions and infrastructure evolution
• Conducting exploratory data analyses to uncover actionable insights for product development

• Initial intro call with Harry, our CEO (30 minutes)
• Technical ML & data science task and discussion with our Data Science Lead (1.5 hours)
• Engineering team discussion (1 hour)
• Call with founders: Luke/Harry (1 hour)