Machine Learning Engineer

Location: Myrtle Point

About Definitive Healthcare :

At Definitive Healthcare (NASDAQ: DH), we’re passionate about turning data, analytics, and expertise into meaningful intelligence that helps our customers achieve success and shape the future of healthcare. We empower them to uncover the right markets, opportunities, and people—paving the way for smarter decisions and greater impact.

We’re headquartered in Framingham, Massachusetts, but we have 3 office locations globally, including locations in Sweden, and India. We’ve grown significantly since our founding in 2011 and have expanded our global client base to 2,400+.

We’re also a great place to work. In 2024, we brought home a number of awards including Built In’s 100 Best Places to Work in Boston, a Stevie Bronze Award for Great Employers, and we were recognized as a Great Place to Work in India.

We foster a collaborative, inclusive culture where diverse perspectives drive innovation. Through programs like Definitive Cares and our employee-led affinity groups we strive to promote connection, education, and inclusion.

Machine Learning Engineer

We are looking for a Machine Learning Engineer to help design and implement AI/ML systems that drive meaningful business outcomes. In this role, you’ll contribute to the development of end-to-end ML solutions—from data preparation and modeling to deployment and performance optimization.

Your work will directly impact customer experience and operational efficiency. The ideal candidate has hands‑on experience in applied machine learning, strong software engineering skills, and a passion for building scalable, production‑ready models. This is a high‑impact role that blends research and engineering, with opportunities to grow and collaborate across teams.

What You’ll Do ML Systems Development & Deployment

• Contribute to the design and implementation of scalable ML systems in cloud environments, focusing on performance and reliability.
• Collaborate with product managers and engineering teams to support ML initiatives aligned with business goals.

Data Pipeline & Feature Engineering

• Help build andmaintaindata pipelines for large-scale datasets, ensuring efficiency and reproducibility.
• Develop meaningful features and label sets across domains such as healthcare and consumer analytics.

Experimentation & Model Management

• Support experimentation efforts, including A/B testing, validation strategies, and model lifecycle management using tools like
  
  MLflowand Databricks.
• Assistin improving model performance through retraining, monitoring, and bias mitigation techniques.

Innovation & Prototyping

• Participate in prototyping and proof‑of‑concept development to explore new ML techniques and technologies.
• Stay current with emerging ML architectures and methodologies.

Cross‑Functional Collaboration

• Work closely with product, engineering, and data teams to deliver integrated ML solutions.
• Contribute to documentation and uphold code quality standards.

What You’ll Need

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (or equivalent practical experience).
• 2–5 years of industry experience in ML Engineering, Data Science, or Data Engineering.
• Proficiency in Python, SQL, andPySpark, with experience using libraries such as scikit‑learn,PyTorch, andXGBoost.
• Experience building ML pipelines and working with tools like
  
  MLflowor similar.
• Familiarity with cloud platforms (AWS, GCP, Azure) and deploying models in production environments.
• Strong communication skills and ability to work effectively in cross‑functional teams.

Preferred Qualifications

• Experience with healthcare claims, EHR, or life sciences datasets.
• Exposure toMLOpspractices such as CI/CD for ML, model versioning, and automated retraining.
• Familiarity with deep learning techniques for time series or sequential data.
• Ability to define performance metrics and evaluate model effectiveness.

Compensation and Benefits

The salary range for this position is $ - $ per year, which represents the base pay the company reasonably and in good faith expects to pay for this role. Actual pay within this range will be determined based on factors such as relevant…