Senior Machine Learning Engineer, Data & Intelligence Products

AcuityMD is a software and data platform that accelerates access to medical technologies, helping MedTech companies improve patient care. The Senior Machine Learning Engineer will lead the development of healthcare data assets by applying machine learning techniques to transform real-world health data into actionable insights, while collaborating with cross-functional teams to enhance product features.

Responsibilities:

• Design, train, and validate predictive and statistical models that turn noisy healthcare data into reliable intelligence products used by MedTech 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

Requirements:

• 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
• 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
• Instinctively build using agentic tools (Claude Code, Codex, etc) and are invested in pushing the boundaries of what is possible with agentic development
• Translate technical recommendations and model behavior clearly and concisely for non-technical product, commercial, and customer audiences
• Hands-on experience merging and blending messy, real-world datasets — time-series, geospatial, demographic, etc — and thrive on extracting signal from noise
• Comfortable working in modern cloud data warehouses with SQL to prepare data for modeling, and can collaborate effectively with data engineers on production pipelines
• Fluent in Python's data and ML stack and opinionated about your preferred approaches, techniques, or model implementations
• Must have an eligible work permit in the USA to be considered for this position
• Experience with healthcare datasets, such as medical insurance claims, prescriptions, EHR/EMR, lab test results, or patient demographic data, is a strong plus