Senior Machine Learning Engineer, Data & Intelligence Products

About AcuityMD

AcuityMD is a software and data platform that accelerates access to medical technologies. We help Med Tech companies understand how their products are used, why customers vary, and identify opportunities for physicians to better serve their patients. Each year, the FDA approves ~6,000 new medical devices. Our solution helps Med Tech companies get these products to physicians more effectively so they can improve patient care with the latest technology.

We’re backed by Benchmark, Redpoint, ICONIQ Growth, and Ajax Health. We’re a high‑growth AI and Data company scaling rapidly.

We are a team of agentic builders who rely heavily on AI development practices to accelerate our ability to deliver value to our customers. We believe in extreme ownership and agency, where every engineer takes responsibility for working throughout the organization to land impact with customers. We’re a close‑knit team that enables high levels of autonomy by constantly communicating our intentions, sharing problems and learnings, and helping each other learn and grow.

In this role, you will help lead the evolution of AcuityMD’s core healthcare data assets by applying statistical and machine learning techniques to convert messy, real‑world health data into insight about the healthcare market. You will design and ship predictive models and data products, improve the quality and interpretability of existing models, and deliver high‑confidence, repeatable intelligence that fuels our Med Tech‑specific modules.

You will identify new approaches and new data sources that extend what our platform can predict and explain. You will work cross‑functionally with engineering, product, and commercial teams.

The Data Team is on a mission to represent medical reality by transforming raw data into assets that directly generate sales for our customers and help bring cutting‑edge medical technology to the patients who need it most. We thrive on turning complexity into simplicity and driving the continuous growth of our products. We acquire terabytes of data from diverse sources and apply modern statistical and machine learning techniques to shape the future of our products and deliver measurable value to customers.

• Design, train, and validate predictive and statistical models that turn noisy healthcare data into reliable intelligence products used by Med Tech commercial teams
• Frame open‑ended business questions as modeling problems — selecting the right approach (classification, regression, clustering, causal inference, ensembles, etc), defining success metrics, and quantifying uncertainty
• Engineer features and conduct applied research across time‑series, geospatial, demographic, insurance claims, and more datasets, to improve the coverage and signal quality of our core data assets
• Own the full model lifecycle: exploratory analysis, baseline modeling, experimentation, validation, deployment, and post‑launch monitoring for drift and performance
• Partner with product managers and cross‑functional stakeholders to translate customer problems into model‑backed product features and to shape the roadmap
• Provide technical leadership and mentorship on statistical and ML methodology for engineers and analysts across the Data organization and across all of AcuityMD
• Document models, assumptions, and data contracts so results are interpretable and reproducible for internal and external audiences

• You have 6+ years of experience in machine learning roles building and shipping statistical or machine learning models into a production environment, ideally as part of product teams delivering to external customers
• You have strong foundations in applied statistics and ML — regression, classification, forecasting, clustering, experimental design, and model evaluation — and you know when each is the right tool.
• You instinctively build using agentic tools (Claude Code, Codex, etc) and are invested in pushing the boundaries of what is possible with agentic development
• You can translate technical recommendations and model behavior clearly and concisely for non‑technical product, commercial, and customer…