Senior Machine Learning Engineer

Summary

Join Accompany Health as a Senior Machine Learning Engineer and help transform healthcare through AI. You will be a mission-critical part of a growing team, collaborating across various departments to build products integrating fragmented healthcare services. This role involves driving AI initiatives, designing scalable machine learning infrastructure, and building robust data infrastructure. You will also partner with cross-functional teams, champion responsible AI development, and optimize the ecosystem for meaningful insights. The position requires 3+ years of data engineering experience, including 2+ years focused on machine learning, a graduate degree in a related field, and strong technical skills. Accompany Health offers a competitive salary range of $175,000-$200,000 a year, plus equity and benefits.

Requirements

• 3+ years of data engineering experience, including 2+ 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
• 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

• 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 for our customers
• Build and optimize AI pipelines and robust monitoring systems
• Help establish data engineering best practices and promote standards that enhance data accessibility across teams
• 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

• $175,000 - $200,000 a year
• Equity
• Benefits