Senior Machine Learning Engineer

• Mission-critical, be part of our growing team (and company).
• Collaborate across the organization with various teams, including Product, Sales, and Clinical Operations, to rewire health care: Your choices will matter, and you will work across multiple teams to help execute the choices
• Drive the change in healthcare: You will build the products to integrate highly fragmented and dispersed healthcare services as an end-to-end experience
• Be part of building a great engineering culture,  maintaining the balance and right tradeoff for building products for speed and tech debt

Responsibilities will include:

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

What makes you a fit for the team:

• Your entrepreneurial mindset and ability to articulate complex technical ideas will be essential as you collaborate across our remote team to solve novel problems at the intersection of AI and compassionate care delivery

Desired skills and experience:

Required
• 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)
• Healthcare experience is valuable but not required
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