Senior Machine Learning Engineer

Accompany Health is dedicated to providing dignified, high-quality care to patients with complex needs. As a Senior Machine Learning Engineer, you will drive AI initiatives, collaborate across teams, and build products that integrate healthcare services to enhance patient care. Your role will involve technical leadership, data strategy, and fostering innovation within the engineering culture.

Responsibilities:

• 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
• 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
• 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
• 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
• 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
• Experience with tools like AWS Sagemaker or Bedrock
• Healthcare experience is valuable but not required