Principal Machine Learning Engineer

Summary

Join Accompany Health as a Principal Machine Learning Engineer and help transform healthcare through AI. You will be a mission-critical part of a growing team, collaborating with various teams to build products that integrate fragmented healthcare services. You will drive change by building end-to-end experiences, contributing to a great engineering culture, and focusing on speed and minimizing tech debt. This role offers technical leadership opportunities, including leading the design and implementation of machine learning infrastructure and solutions. You will also build and maintain data infrastructure, champion responsible AI development, and partner with cross-functional teams. The position requires 5+ years of data engineering experience, including 3+ years focused on machine learning, and a graduate degree in a related field.

Requirements

• 5+ years of data engineering experience, including 3+ years focused on machine learning
• Graduate degree in Computer Science, Statistics, or related quantitative field
• You are entrepreneurial and mission-driven and can present your ideas with clarity and confidence
• Problem solver who can thrive in a remote but collaborative team environment
• Hands-on expertise in:Developing and implementing modern LLM models and transformers
• Developing and deploying ML models in a production environment Strong Python, SQL, and ability to create efficient and maintainable code for machine learning applications
• Develop, productize and maintain ML pipelines for model training, evaluation, deployment (such as AWS Sagemaker, Bedrock)
• Design and Implement best practices for model versioning, experimentation, and reproducibility
• Continuously improve our ML infrastructure for stability, scalability, observability, and security
• Develop internal tooling and libraries to enhance ML workflow efficiency
• Performing root cause analysis identify opportunities for improvement

Responsibilities

• Be the AI champion and empower others to leverage the data to its full potential with a review of AI models
• Lead the technical design and implementation of reliable, scalable, and efficient Machine Learning infrastructure, products, and software solutions for external and internal customers
• Lead the development of efficient, reliable AI pipeline architecture with strong monitoring capabilities
• Provide technical leadership to develop data engineering best practices and standards that promote accessibility and usability
• Build and maintain robust, scalable data infrastructure to support current and future needs
• 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 cross-functional teams, including Executive, Product, Clinical, Data, and Design, to assist with data-related technical issues and support their data infrastructure needs
• Identify, design, and implement process improvements to enhance efficiency and scalability
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
• Develop Safeguards to ensure that AI models are fair and appropriate so that all patients receive high-quality and timely care
• Optimize our ecosystem to generate meaningful insights and drive innovation
• Develop efficient, reliable AI pipelines with strong monitoring and observability
• Navigate and optimize our data ecosystem to drive meaningful insights
• Work with and assemble large, complex data sets that meet functional / non-functional needs

Preferred Qualifications

Healthcare experience is valuable but not required

Benefits

• $195,000 - $230,000 a year
• + equity