Machine Learning Engineer, Sr. - Remote

Our client is seeking a Senior Machine Learning Engineer to build AI products that support clinical research and help accelerate how new therapies reach patients. This role is focused on turning advanced AI research into scalable, production-ready machine learning solutions for real-world healthcare applications.

The ideal candidate has strong hands-on experience building and deploying ML systems at scale and understands the requirements of working in healthcare and regulated environments. You will work across the full machine learning lifecycle, from concept and development through deployment, monitoring, and scaling, while collaborating with data scientists, product managers, designers, engineers, and healthcare domain experts.

Key Responsibilities

• Build and deploy AI-driven products that support clinical trials and patient outcomes.

• Develop scalable machine learning solutions for complex clinical research problems.

• Build advanced ML models and LLM-powered agents for patient recruitment, enrollment forecasting, and study feasibility.

• Contribute to the development and expansion of AI knowledge base architecture.

• Build robust data pipelines using modern cloud tools and MLOps practices.

• Develop and deploy models at scale using Python, AWS services, dbt, Prefect, and related technologies.

• Use AWS services including Athena, Bedrock, and SageMaker for machine learning and data workflows.

• Implement CI/CD automation, monitoring, automated testing, and other practices that support reliable ML deployments.

• Integrate AI capabilities into platform products, including Care Access products, to support clinical research workflows.

• Work closely with data scientists, product managers, designers, engineers, and domain experts.

• Stay current with developments in machine learning and AI, including LLMs, NLP, and probabilistic modeling.

• Experiment with emerging techniques and turn promising prototypes into production features.

• Continuously automate, improve, and optimize machine learning processes.

• Take ML products through the full lifecycle: concept, development, deployment, monitoring, and scaling.

• 5+ years of hands-on experience building and deploying machine learning solutions in production at scale.

• Healthcare experience is required, including an understanding of regulated environments, compliance requirements, security considerations, model governance, and bias and fairness concerns.

• Proven experience implementing end-to-end ML pipelines from data ingestion through model serving.

• Strong proficiency in Python and its machine learning ecosystem, including pandas, scikit-learn, TensorFlow, and/or PyTorch.

• Experience working with large datasets and writing complex SQL queries.

• Strong understanding of machine learning fundamentals, including model selection, training, evaluation, and feature engineering.

• Knowledge of statistical modeling.

• Familiarity with natural language processing and large language models.

• Experience with AWS and containerization tools such as Docker.

• Experience with MLOps practices, including CI/CD, automated testing, and model performance and data drift monitoring.

• Strong analytical and problem-solving skills, with the ability to develop effective and efficient ML solutions.

• Ability to balance scientific rigor with practical engineering considerations to deliver accurate, performant, and maintainable production systems.

• Strong collaboration, communication, initiative, and ability to work independently in a remote environment.

Preferred Qualifications

• Experience with functional programming, such as Clojure.

• Experience working with AWS services including Athena, Bedrock, and SageMaker.

• Experience with dbt and Prefect.

• Experience developing LLM-powered agents and AI knowledge base architectures.

• Experience with probabilistic modeling and other emerging ML/AI techniques.