Sr. Machine Learning Engineer
Akasa
A complete application in a minute
Tailored resume and cover letter, ready to send.
Benefits offered by this job
Job summary
Akasa in San Francisco Bay Area is seeking a Sr. Machine Learning Engineer to translate clinical data into actionable AI models. You will join PhD researchers and ML engineers to deploy production ML systems that process large proprietary medical datasets, including structured documents, natural language, and images.
The role blends research, software engineering, and healthcare outcomes. You’ll collaborate with the team to deploy models that improve documentation, coding accuracy, and claim
Qualifications
- Master's degree in Computer Science or a related field.
- 5+ years of experience in machine learning and data engineering.
- Experience launching production ML systems from the ground up.
- Experience with Large Language Models, including deployment or fine-tuning of LLMs.
- Proficiency in Python and C++.
- Development experience with cloud platforms such as Spark, AWS and Kubernetes.
- Knowledge of ML frameworks such as Scikit-Learn, PyTorch and TensorFlow.
Responsibilities
- Develop state-of-the-art ML solutions addressing large-scale healthcare problems.
- Own ML services end-to-end—from discovery to deployment.
- Build data pipelines for data collection, preprocessing, and delivery with measurable quality.
- Write production-ready software with efficient algorithms.
- Develop ML models across LLMs, probabilistic inference, and computer vision for tasks like document extraction and coding.
- Build application-specific ML models and deploy predictions in novel ways.
Skills
Education
Tools
Job description
Improving Healthcare
My journey into CDI was personal. I have two children with special healthcare needs and their conditions were under documented. No one really wanted to talk about my daughter's brain injury because it wasn't documented. I battled to get her the care and the resources that she needed. The good news is today she's getting her masters and she's going to become a teacher. Had I not battled and pushed and fought and clawed to get her those services, she might not be where she is today.
1%
1%
they think it’s necessary
1%
lot of responsibility
AKASA core beliefs and behaviors
We weave these values into the fabric of everything we do. They help us achieve our vision and uphold our mission of transforming healthcare operations.
We are relentlessly focused on enabling health systems to transform their operations.
Our mission is audacious. We only succeed by finding the best solution and focusing on what matters.
To truly transform healthcare, we must act quickly and constantly evolve.
We know great work isn’t done alone. Nothing is someone else’s problem.
- Flexible PTO
- Robust healthcare plans, including 100% free options
- Employer contribution to healthcare spending accounts
- Mental health support through Spring Health
- Free One Medical membership
- Generous parental leave policy
- Company-sponsored 401k plan
- Commuter benefits with employer contribution
- Internet/cell phone reimbursement
- Equipment stipend to set up your workstation however you want
We know that diverse teams succeed.
We have built a community and culture in which all AKASAns, regardless of background or identity, can bring their authentic selves to work. We believe this culture of belonging is critical in order for our team members to do the best work of their lives.
If you're from a non-traditional background or underrepresented group, please apply to one of our open roles. Not sure if you're 100% qualified? Apply anyway. Your skills may be exactly what we need.
When a patient comes into the hospital, we take care of them, no matter what. But patients are getting sicker, and the medical record doesn’t always capture everything it took to care for them. That gap can cost hospitals appropriate reimbursement and understate how sick patients really were. That’s where AKASA comes in. We’re building AI that helps documentation and coding reflect the care delivered, and I bring the clinical context. Our technical team builds first-of-its-kind products for consequential problems in healthcare, and our in-house clinical experts train the models.
Remote - United States
Full time
Remote
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.
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.
- 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
- 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
- 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
'/%3e%3cpath%20d='M101.744%2012.4726L102.894%2016.1947L99.0021%2013.2201L101.744%2012.4726ZM105.3%208.40937H100.488L99.0026%203.59473L97.5116%208.41047L92.7%208.40385L96.5965%2011.3834L95.1055%2016.1942L99.0021%2013.2196L101.408%2011.3834L105.3%208.40992V8.40937Z'%20fill='white'/%3e%3cdefs%3e%3clinearGradient%20id='paint0_linear_5593_1381'%20x1='90'%20y1='9.44471'%20x2='99'%20y2='9.44471'%20gradientUnits='userSpaceOnUse'%3e%3cstop%20stop-color='%2300AD70'/%3e%3cstop%20offset='0.998594'%20stop-color='%2300B67A'/%3e%3cstop%20offset='1'%20stop-color='%23DCDCE6'/%3e%3c/linearGradient%3e%3c/defs%3e%3c/svg%3e){kind=small}
