Definitive Healthcare is looking to hire a Machine Learning Engineer to help design and implement AI/ML systems that drive meaningful business outcomes, impacting customer experience and operational efficiency.
Requirements
- Proficiency in Python, SQL, and PySpark, with experience using libraries such as scikit-learn, PyTorch, and XGBoost.
- Experience building ML pipelines and working with tools like MLflow or similar.
- Familiarity with cloud platforms (AWS, GCP, Azure) and deploying models in production environments.
- Experience with healthcare claims, EHR, or life sciences datasets.
- Exposure to MLOps practices 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.
Responsibilities
- 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.
- Help build and maintain data pipelines for large-scale datasets, ensuring efficiency and reproducibility.
- Develop meaningful features and label sets across domains such as healthcare and consumer analytics.
- Support experimentation efforts, including A/B testing, validation strategies, and model lifecycle management using tools like MLflow and Databricks.
- Assist in improving model performance through retraining, monitoring, and bias mitigation techniques.
- Participate in prototyping and proof-of-concept development to explore new ML techniques and technologies.
Other
- 2–5 years of industry experience in ML Engineering, Data Science, or Data Engineering.
- Strong communication skills and ability to work effectively in cross-functional teams.
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (or equivalent practical experience).
