Machine Learning Engineer (AI)

Location: Hybrid in San Francisco, CA, United States

Base salary: $220K–$300K annually, plus equity.

Company

Freed builds AI-powered tools that reduce administrative work for healthcare professionals and give clinicians more time for patient care.

What you will do

• Develop, evaluate, and improve machine learning models and AI-powered product capabilities.
• Build and maintain production ML pipelines, services, and supporting infrastructure.
• Design experiments and evaluation frameworks for model quality, reliability, and performance.
• Collaborate with product and engineering teams to translate user needs into practical technical solutions.
• Improve the scalability, efficiency, and reliability of ML systems in production.
• Investigate model failures, incorporate real-world feedback, and contribute to ML lifecycle engineering practices.

Requirements

• Strong software engineering fundamentals and experience building production systems.
• Hands-on experience developing and deploying machine learning solutions.
• Proficiency in Python and familiarity with modern ML frameworks and tooling.
• Experience evaluating model performance and improving systems through experimentation.
• Understanding of ML infrastructure, deployment, monitoring, and production reliability.
• Ability to work independently, communicate clearly, and collaborate across disciplines.
• Comfort working in a fast-moving environment with evolving technical and product requirements.

Nice to have

• Experience with large language models, generative AI, or speech-related ML systems.
• Experience with model evaluation, fine-tuning, or inference optimization.
• Familiarity with healthcare technology or other high-reliability product environments.
• Experience building ML products in an early-stage startup.

Culture & Benefits

• Work on AI products with a direct connection to clinicians and their patient-care workflows.
• Opportunity to take ownership, influence technical direction, and shape product development.
• Hybrid work in San Francisco.
• Full-time employment with equity in addition to base salary.