Senior Machine Learning Engineer

Accompany Health is on a mission to give patients with complex needs the dignified, high-quality care they deserve. As a Senior Machine Learning Engineer, you will help transform healthcare through AI by collaborating across the organization and driving AI initiatives to enhance healthcare services.

Responsibilities:

• Technical Leadership
• Drive AI initiatives and collaborate with teams to leverage data effectively through model development and evaluation
• Design and implement scalable Machine Learning infrastructure and solutions, ensuring reliability and performance
• Help establish data engineering best practices and promote standards that enhance data accessibility across teams
• Data Strategy & Architecture
• Create and maintain optimal AI pipeline architecture with high observability and robust operational characteristics
• Champion responsible AI development by implementing and reviewing models that maximize data value while ensuring fairness and equity
• Assemble large, complex data sets that address functional and strategic requirements
• Collaboration & Enablement
• Partner with other teams such as; Executive, Product, Clinical, Data, and Design
• Identify, design, and implement process improvements to enhance efficiency and scalability
• Create tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
• Quality & Innovation
• Develop efficient, reliable AI pipelines with strong monitoring and observability
• Navigate and optimize our data ecosystem to drive meaningful insights
• Design and implement comprehensive evaluation frameworks and benchmarks to rigorously assess model performance, accuracy and reliability

Requirements:

• 5+ years of software engineering experience, with a focus on building production-grade machine learning systems, backend infrastructure, or MLOps
• Graduate degree in Computer Science, Statistics, or related quantitative field
• Strong proficiency in Python and SQL, with the ability to create efficient and maintainable code for machine learning applications
• Developing and maintaining ML pipelines for model training, evaluation, deployment (experience with tools like AWS Sagemaker or Bedrock is preferred)
• You have hands-on experience in: Developing and implementing modern LLM models and transformers and deploying ML models in a production environment
• Designing and implementing best practices for model versioning, experimentation, and reproducibility
• Continuously improving our ML infrastructure for stability, scalability, observability, and security
• Developing internal tooling and libraries to enhance ML workflow efficiency
• Healthcare experience is valuable but not required