Principal Machine Learning Engineer

Role overview Set the technical direction for machine learning systems that personalize care, inform treatment, and automate parts of service delivery. This principal-level engineering role spans architecture and hands-on development, with a focus on building reliable ML platforms that support model training, real-time predictions, evaluation, and continued product growth.

Responsibilities - Define architecture for machine learning and language model applications used in personalization and treatment recommendations. - Establish design patterns and infrastructure practices for secure, scalable, resilient, and maintainable systems. - Prototype and guide implementation of model pipelines and platform components using Python and modern ML frameworks. - Build and evolve infrastructure for continuous training, real-time inference, evaluation, and observability. - Work with product, platform, and clinical partners to connect technical choices to product strategy. - Lead cross-team efforts to simplify systems, improve development speed, and strengthen quality practices; mentor senior engineers.

Requirements - At least ten years of machine learning or software engineering experience, including technical leadership and system architecture across teams. - Expert Python skills and advanced experience with an ML framework such as PyTorch or TensorFlow. - A record of designing and scaling production ML platforms for training, deployment, inference, and monitoring. - Deep knowledge of large language models and natural language processing, including transformers, summarization, conversational systems, and embedding-based retrieval. - Strong understanding of ML infrastructure, reliability, performance, and observability; experience with tools such as Databricks, MLflow, or SageMaker, or equivalents. - Strong communication and cross-functional leadership skills.

Nice to have - A master’s degree or doctorate in computer science, machine learning, or a related discipline; this is not required.

Benefits and work setup - Salary and equity compensation, paid time off, company holidays, and quarterly mental health days. - Medical, dental, and vision coverage, parental leave, retirement plan matching, and an employee stock purchase program. - Team retreats.