Why This Job is Featured on The SaaS Jobs
AKASA sits in the applied GenAI SaaS segment, building software that embeds large language models into operational workflows for healthcare systems. For the broader SaaS ecosystem, this is notable because it reflects a shift from “AI features” toward AI-native products where model quality, evaluation, and deployment directly determine customer outcomes and retention in a regulated, high-stakes domain.
For an ML researcher building a long-term SaaS career, the role signals work that connects research choices to product behavior in production: data creation, training, evaluation, iteration, and the feedback loops that come from real customer usage. Experience translating LLM advances into measurable workflow improvements tends to transfer across modern SaaS categories—especially where automation, document understanding, and human-in-the-loop review are central to the product.
This role is best suited to researchers who prefer applied, end-to-end ownership over narrowly scoped experimentation, and who value close collaboration with engineers and domain experts to shape what “good” looks like in real environments. It also fits candidates who want their research output to influence shipped capabilities, not only internal benchmarks or publications.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About AKASA
At AKASA, our mission is to build the future of healthcare with AI. As the leading provider of generative AI solutions for the healthcare revenue cycle, we 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 have raised over $205M in funding from investors such as Andreessen Horowitz, BOND, and Costanoa Ventures.
This is the most exciting time to join AKASA. Revenue bookings for our new AI-native product suite have grown over 20x since launching in 2024. In this time, we have broken our record for the largest deal in company history three times consecutively. This growth is driven by the massive improvement we are generating for our customers across clinical quality and documentation accuracy, both top priority areas for health system leaders.
Our deployments have been recognized nationally as "one of the most comprehensive real-world uses of GenAI in healthcare finance to date" (link). Our customer base represents more than $120B+ in net patient revenue and includes the most innovative health systems in the country, like Cleveland Clinic, Duke, Stanford, and Johns Hopkins.
Some of our most recent recognitions include being named the #1 most promising healthcare RCM startup of 2025 by Black Book Market Research and one of the fastest-growing GenAI startups to watch by AIM Research. Our CEO was ranked among the “Top 50 Healthcare Technology CEOs” by the Healthcare Technology Report, and we have been certified as a “Great Place to Work” for the past five years in a row, just to name a few.
We’re building on this momentum to redefine what’s possible in healthcare. We’re looking for exceptional people to help us accelerate that reality.
About the Role
As a Senior Machine Learning Researcher at AKASA, you’ll play a crucial role in pioneering advanced AI solutions that are transforming healthcare. You’ll collaborate closely with a talented team of PhD researchers, ML engineers, and healthcare experts to create models that directly enhance human efficiency and precision in complex operational workflows across the healthcare system. Our mission is to empower healthcare professionals with tools that amplify their capabilities, making them faster, more comprehensive, and more effective in their roles.
At AKASA, our research and development balance cutting-edge LLM innovation with practical impact on healthcare operations. You’ll contribute to developing and adapting advanced language models, including pretraining and fine-tuning work on architectures like Llama. In this role, you’ll work end-to-end on model design, data creation, training, evaluation, and iteration, ensuring that your research advances not only our models but also the real-world tasks they support. You’ll have the opportunity to influence new research directions, support high-impact publications, and contribute directly to AKASA’s product offerings, bringing your work to life in tools used across healthcare systems.
This is a US-based remote position with significant opportunities to impact healthcare through rigorous ML research and product innovation. We welcome candidates eager to advance AI’s role in healthcare within a collaborative, mission-driven environment.
What You'll Do
Drive Applied Research: Lead the design, training, and evaluation of large language models to solve healthcare-specific challenges, advancing the state of the art in clinical Natural Language Understanding.
Leverage Human-in-the-Loop Feedback: Work closely with cross-functional teams to integrate Human-in-the-Loop data, using it to guide model improvements and explore new methods for optimizing performance.
Collaborate Across Teams: Partner with healthcare experts and other stakeholders to integrate qualitative insights, ensuring models align with real-world needs and deliver meaningful results.
Stay on the Cutting Edge: Regularly evaluate advancements in ML to determine their relevance to our work, maintaining AKASA’s leading edge in responsible, high-impact healthcare AI.
Contribute to Broader Impact: Publish and share research findings in the broader AI community, helping to advance healthcare applications of AI through peer-reviewed publications.
Skills & Qualifications
A passion for tackling meaningful healthcare challenges and leveraging AI to make a positive impact on the healthcare system.
Proven experience training and fine-tuning large language models, with expertise in model architecture, optimization techniques, and performance evaluation. Experience with modeling in the healthcare domain, clinical natural language understanding, and healthcare data and data standards (e.g., EDI, FHIR) is strongly preferred.
Ph.D. or equivalent industry experience in fields related to machine learning, natural language processing, computer vision, computer science, electrical engineering, statistics, mathematics, optimization, or data science, plus 2-3 years of experience. Peer-reviewed publications in top AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, NAACL, and EMNLP) strongly preferred.
Strong programming skills in Python, with proficiency in deep learning frameworks and tools such as PyTorch, TensorFlow, PyTorch Lightning, Hugging Face Transformers, and Kubernetes/Kubeflow, as well as experience with cloud platforms (AWS, GCP) and multi-GPU environments.
A track record of translating research into real-world applications, with experience in rapid prototyping, experimentation, and writing production-ready code.
Ability to work effectively in a cross-functional, fast-paced environment, with strong written and verbal communication skills.
What We Offer
Unlimited 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
Company-paid holidays401(K) plan
Compensation
Based on market data and other factors, the salary range for this position is $175,000-$230,000 + Equity. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.
The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.
We’re committed to doing the best work of our lives, together. Come see if we're the right team for you.
AKASA is a proud equal opportunity employer and we believe that a diverse and inclusive workforce is an imperative. We welcome people of different backgrounds, genders, races, ethnicities, abilities, sexual orientations, and perspectives, just to name a few. We do not discriminate based upon any protected class and we encourage candidates of all identities and backgrounds to apply. AKASA considers qualified applicants regardless of criminal histories in accordance with the San Francisco Fair Chance Ordinance.
AKASA is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at recruiting@akasa.com.
