Senior Machine Learning Engineer

Definitive Healthcare, US•Framingham, MA

17h

About The Position

At Definitive Healthcare, we are dedicated to transforming data, analytics, and expertise into valuable intelligence that empowers our customers to succeed and shape the future of healthcare. We help them identify the right markets, opportunities, and individuals, leading to smarter decisions and greater impact. Headquartered near Boston, Massachusetts, Definitive Healthcare operates globally, supporting over 2,400 customers since 2011. The company has received multiple workplace honors, including being named one of Built In’s 100 Best Places to Work in Boston for 2024 and 2025, a Stevie Bronze Award for Great Employers, and recognition as a Great Place to Work in India. We cultivate a collaborative and inclusive culture that values diverse perspectives and drives innovation through programs like DefinitiveCares and employee-led affinity groups. We are seeking a Senior Machine Learning Engineer to lead the design and implementation of advanced AI/ML systems that deliver significant business outcomes. This role involves owning end-to-end ML solutions, from architecture and modeling to production deployment and performance optimization. Your work will have a broad and lasting impact on customer experience and operational efficiency by shaping technical strategy and architecting comprehensive ML solutions. The ideal candidate will possess extensive experience in applied machine learning, strong software engineering skills, and a proven ability to mentor teams and deploy production-ready models at scale. This is a high-impact, full-stack ML position that combines research, engineering, and leadership, offering the opportunity to influence both the company’s technical foundation and product direction.

Requirements

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (or equivalent practical experience).
5+ years of industry experience as an ML Engineer, Data Scientist, or Data Engineer, with a focus on deploying and scaling ML systems.
Deep expertise in Python, SQL, and PySpark for distributed data processing, with proficiency in libraries like scikit-learn, PyTorch, and XGBoost.
Proven experience designing robust ML pipelines, leveraging tools like MLflow or equivalent.
Strong command of ML frameworks (e.g., scikit-learn, TensorFlow, XGBoost, PyTorch).
Hands-on experience deploying models in cloud-based environments (AWS, GCP, Azure, and Databricks).
Proven ability to manage end-to-end ML lifecycles at scale, including data ingestion, training, evaluation, deployment, and monitoring.
Excellent communication skills and demonstrated ability to influence cross-functional teams.

Nice To Haves

Experience working with healthcare claims, EHR, or life sciences datasets.
Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, or related technical field.
Strong knowledge of MLOps practices including CI/CD for ML, automated retraining, and model versioning.
Experience with deep learning architectures for time series forecasting, sequential data, or hierarchical modeling.
Proficient in designing evaluation protocols and defining performance metrics to rigorously assess model effectiveness and drive data-driven decision-making.
Comfortable operating in fast-paced, high-ownership environments, and able to prioritize multiple high-impact projects.

Responsibilities

Lead the design and implementation of scalable, production-grade ML systems in cloud environments with a focus on performance, reliability, and reproducibility.
Collaborate with product managers and senior stakeholders to define and prioritize ML initiatives aligned with business goals.
Oversee the architecture and evolution of data pipelines for multi-terabyte datasets, ensuring efficiency and reliability.
Guide the development of high-impact features and label sets across diverse domains such as healthcare and consumer analytics.
Lead experimentation strategy, including design of A/B tests, advanced validation methods, and lifecycle management using tools like MLflow and Databricks.
Drive continual model improvement through advanced techniques such as automated retraining, model decay analysis, and bias mitigation.
Champion rapid prototyping and proof-of-concept development to evaluate emerging technologies and ML techniques.
Lead technical explorations into new ML architectures (e.g., foundation models, causal inference, time series deep learning).
Serve as a technical leader and trusted advisor, working closely with product, engineering, data, and executive teams to shape end-to-end ML solutions.
Set standards for code quality, performance, and documentation, and mentor junior engineers in best practices.

Benefits

medical, dental, and vision coverage
unlimited paid time off
participation in the company’s 401(k) plan with employer contribution
annual bonus program, subject to individual and company performance
Industry leading products
Work hard, and have fun doing it
Incredibly fast growth means limitless opportunity
Flexible and dynamic culture
Work alongside some of the most talented and dedicated teammates
Definitive Cares, our community service group, gives all of us a chance to give back
Competitive benefits package including great healthcare benefits and a 401(k) match