Senior Machine Learning Engineer, AKASA

• Master's degree in Computer Science or similar
• 5+ years of work experience in machine learning and data engineering
• Have experience launching production systems from the ground up
• 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
• Full-stack development experience for an end-to-end ML solution
• Ideal experience with Large Language Models, including both open source model deployment and agentic workflows

• As a Sr. Machine Learning Engineer, you'll report to our VP of Engineering and work with machine learning (ML) PhDs from top schools (e.g., Stanford), and experienced machine learning engineers from top companies (e.g., Google).
• You will put machine learning into practice, so your code directly affects our customers immediately. You will work with large proprietary medical and clinical datasets containing both structured documents, natural language and images
• 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
• Participate in developing state-of-the-art ML solutions to address large-scale healthcare problems
• 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 computer vision, large-language models, and probabilistic inference to solve problems like medical document entity extraction, medical coding and claim outcome prediction
• Own ML services end-to-end, including problem discovery, data pipeline development, inference optimizations, model experimentation, and service deployment
• 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

• Unlimited paid time off (PTO)
• Expansive coverage for health, dental, and vision
• Employer contribution to Health Savings Accounts (HSA)
• Generous parent leave policy
• Full employee coverage for life insurance
• Company-paid holidays
• 401(K) plan

Total funding: $205m

The US healthcare system is both financially and operationally complex. It is estimated to cost patients and providers $500 billion annually in medical billing and insurance administrative expenses. AKASA, formerly Alpha Health, addresses this issue with its Unified Automation technology