Senior Machine Learning Engineer, Data & Intelligence Products

AcuityMDAcuityMD·Remote(United States)
AI & Machine Learning

WFA Digital Insight

The demand for machine learning specialists in healthcare has skyrocketed, with a 25% increase in job postings in the last year alone. As the healthcare industry becomes increasingly reliant on data-driven insights, the role of machine learning engineers is becoming pivotal. AcuityMD is at the forefront of this trend, leveraging AI and data to accelerate access to medical technologies. With a strong foundation in applied statistics and machine learning, candidates can capitalize on this trend and drive real impact. Before applying, candidates should be aware of the company's emphasis on extreme ownership and agency, as well as its commitment to continuous growth and learning.

Job Description

About the Role

The Senior Machine Learning Engineer will play a critical role in leading the evolution of AcuityMD's core healthcare data assets. By applying statistical and machine learning techniques, the successful candidate will turn messy, real-world health data into actionable insights that drive sales for MedTech companies. As part of a close-knit team, the engineer will work cross-functionally with engineering, product, and commercial teams to deliver high-confidence, repeatable intelligence. With a focus on autonomy and agency, the engineer will take ownership of their work, collaborating with others to drive continuous growth and learning.

The Data Team at AcuityMD is on a mission to represent medical reality by transforming raw data into assets that directly generate sales for customers. By turning complexity into simplicity, the team drives the continuous growth of its products, acquiring terabytes of data from diverse sources and applying modern statistical and machine learning techniques to shape the future of its products.

What You Will Do

  • Design, train, and validate predictive and statistical models that turn noisy healthcare data into reliable intelligence products
  • Frame open-ended business questions as modeling problems, selecting the right approach and defining success metrics
  • Engineer features and conduct applied research across various datasets to improve the coverage and signal quality of core data assets
  • Own the full model lifecycle, from exploratory analysis to post-launch monitoring
  • Partner with product managers and cross-functional stakeholders to translate customer problems into model-backed product features
  • Provide technical leadership and mentorship on statistical and ML methodology
  • Document models, assumptions, and data contracts to ensure results are interpretable and reproducible
  • Identify new approaches and data sources to extend the platform's predictive capabilities
  • Work closely with the engineering team to deploy and maintain models in a production environment
  • Collaborate with the commercial team to deliver high-confidence, repeatable intelligence that fuels MedTech-specific modules

What We Are Looking For

  • 6+ years of experience in machine learning roles, building and shipping statistical or machine learning models into a production environment
  • Strong foundations in applied statistics and ML, including regression, classification, forecasting, clustering, and experimental design
  • Experience with agentic tools, such as Claude Code or Codex
  • Ability to build and deploy models using a range of technologies and frameworks
  • Strong communication and collaboration skills, with the ability to work cross-functionally with engineering, product, and commercial teams
  • Experience with healthcare data and the ability to navigate complex regulatory environments
  • Strong problem-solving skills, with the ability to frame open-ended business questions as modeling problems
  • Experience with data visualization and communication of complex results to non-technical stakeholders

Nice to Have

  • Experience with natural language processing and text analysis
  • Familiarity with cloud-based technologies, such as AWS or Google Cloud
  • Experience with containerization using Docker
  • Knowledge of DevOps practices and Agile development methodologies
  • Certification in machine learning or a related field

Benefits and Perks

  • Competitive salary and benefits package
  • Equity and stock options
  • Flexible PTO and remote work arrangements
  • Professional development opportunities, including training and conference attendance
  • Access to cutting-edge technologies and tools
  • Collaborative and dynamic work environment
  • Opportunity to work on high-impact projects that drive real change in the healthcare industry

How to Stand Out

  • Tip: Highlight your experience with machine learning and statistical techniques, particularly in the context of healthcare data.
  • Tip: Be prepared to discuss your approach to model development, deployment, and maintenance, as well as your experience with agentic tools.
  • Tip: Showcase your ability to communicate complex results to non-technical stakeholders, using data visualization and storytelling techniques.
  • Tip: Emphasize your experience working cross-functionally with engineering, product, and commercial teams, and your ability to navigate complex regulatory environments.
  • Tip: Research the company's culture and values, and be prepared to discuss how you embody the principles of extreme ownership and agency.
  • Tip: Be prepared to discuss your salary expectations and negotiated benefits, considering the company's competitive salary and benefits package.

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