Applied AI Engineer

Description

About the company

Healthcare operations have always depended on people to bridge the gaps that technology couldn't. It relies on complex manual work to carry out critical internal processes, yet most health systems don’t have enough resources to properly automate these tasks, leaving them stuck in outdated, labor-intensive SOPs.

The company structures the chaos, automates the manual handoffs, and deploys end-to-end workflows across every system, providing the integrated intelligence layer to improve processes over time. By delegating to autonomous AI systems those mission-critical workflows that previously expended valuable human time, the company allows doctors and administrators to do what they do best: Focus on Patients.

Our team is in-office 4 days a week (Monday - Friday, Wednesday optional WFH) in either San Francisco, California or New York, New York.

About the role

As a Lead Software Engineer working on AI systems, you will play a foundational role in research, experimentation and rapid improvement of AI systems towards building a capable, reliable AI automation platform, while also raising the technical bar for the engineers around you. You are expected to have deep proficiency in the fundamentals of software engineering, a willingness to pick up new concepts as needed, and a proven ability to drive technical projects and set technical direction in ambitious environments.

Responsibilities

• Design experiments and test ideas to optimize key internal AI benchmarks
• Design and improve evaluation frameworks to accelerate the speed and direction of experimentation
• Train, fine-tune, and optimize machine learning models. Perform rigorous evaluation and testing to ensure model accuracy, generalization, and performance.
• Collaborate and contribute on the core product development to deliver higher platform capabilities
• Set up observability and monitoring systems to safety check model behavior in critical settings
• Set technical direction across experimentation and evaluation work, raising the bar on rigor, tooling, and best practices for the team
• Mentor and unblock other engineers, acting as a senior voice on ambiguous technical tradeoffs

Requirements

• 5+ years of proven track record shipping high-quality code in challenging projects
• A track record of being the senior, steady hand on a team, comfortable operating with less oversight and setting the bar for others
• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field
• Solid fundamentals in algorithms, data structures, system design
• Attention to detail and a first-principles thinking towards real world deployment of intelligent systems
• Experience shipping ML models to production
• Bonus
• Previous experience working with distributed computing systems in production