Sr. Machine Learning Engineer

About AKASA

AKASA is building the future of healthcare by developing AI-native solutions for some of healthcare’s most complex, consequential work. Our customers include the most innovative health systems in the country, like Cleveland Clinic, Mayo Clinic, NewYork-Presbyterian, Duke, Stanford, and Johns Hopkins. Our customer base represents 1 in 10 inpatient discharges across the United States and more than $180B+ in net patient revenue.

Our products help health systems comprehensively capture and communicate the full patient clinical journey. By empowering health systems to streamline their operations, they can focus on what matters most - delivering quality patient care.

We train internal models and build domain-specific harnesses to power our products and best capture clinical nuance for each customer. We hire people with high agency and good judgment. Everyone here is an owner and builder who is looking to help solve high stakes challenges every day.

We have raised over $250M in funding from investors such as Andreessen Horowitz, BOND, and Coatue. Our deployments have been recognized nationally as "one of the most comprehensive real-world uses of GenAI in healthcare finance to date" ( link

).

Some of our recent recognitions include being named one of America's Top Startup Employers 2026 by Forbes, a Top Healthcare Technology Company of 2026 by Healthcare Technology Report, the #1 most promising healthcare RCM startup of 2025 by Black Book Market Research, and we have been certified as a “Great Place to Work” for the past 6 years in a row.

About the Role

As a Sr. Machine Learning Engineer, you'll report to our Engineering Manager and work with a talented team of PhD Researchers, ML Engineers, and healthcare experts. You will put machine learning into practice, so your code directly affects our customers immediately. You’ll work with large proprietary medical and clinical datasets containing structured documents, natural language and images.

Our mission is to empower healthcare professionals with tools that amplify their capabilities, making them faster, more comprehensive, and more effective in their roles.

The AKASA office is located in South San Francisco. While we support remote work on a variety of teams, we have a strong Bay Area presence across the company. The local R&D teams come into the office every Wednesday for co-working days, which this role will be expected to attend.

What You'll Do

• Participate in developing state-of-the-art ML solutions to address large-scale healthcare problems
• Own ML services end-to-end, including problem discovery, data pipeline development, inference optimizations, model experimentation, and service deployment
• Help develop pipelines that collect, preprocess, and deliver data with a measurable quality
• Write production-ready software with well-tested and efficient algorithms
• Develop state-of-the-art ML algorithms across large-language models, probabilistic inference and computer vision to solve problems like medical document entity extraction, medical coding and claim outcome prediction
• Help build novel, application-specific ML models - all of our products are built from the ground up with ML at their core, enabling us to deploy our predictions in new and interesting ways
• Skills & Qualifications
• Master's degree in Computer Science or similar
• 5+ years of work experience in machine learning and data engineering
• Experience launching production ML systems from the ground up
• Experience with Large Language Models, including both open source model deployment and agentic workflows; ideal: experience directly training or fine-tuning LLMs
• Proficiency in one or more programming languages such as Python and C++
• Development experience with cloud platforms such as Spark, AWS & k8s
• Knowledge of ML frameworks such as Scikit-Learn, Pytorch & TensorFlow

What We Offer

• Flexible paid time off (PTO)
• Expansive coverage for health, dental, and vision
• Employer contribution to Health Savings Accounts (HSA)
• Generous parental leave policy
• Full employee coverage for life insurance
• Home office stipend
• Cell phone/internet reimbursement
• Company-paid holidays

401(K) plan