Senior Machine Learning Researcher, AKASA
$175-230k
+ Equity
AI-powered automation for the healthcare revenue cycle
Be an early applicant
AI-powered automation for the healthcare revenue cycle
201-500 employees
Be an early applicant
$175-230k
+ Equity
201-500 employees
Company mission
To enable human health by building the future of healthcare with AI.
Role
Who you are
- We welcome candidates eager to advance AI’s role in healthcare within a collaborative, mission-driven environment
- 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 the job involves
- 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
- 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
Our take
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
The technology is designed to streamline revenue cycle operations by combining human expertise with AI-driven automation. It deploys machine-learning tools supported by revenue cycle specialists who can handle more complex cases and refine the algorithms.
This blend of human and machine intelligence is a stand-out approach, which could well serve as a blueprint for other sectors. Meanwhile, AKASA will continue to help reshape the healthcare industry by solving its complex operational challenges.
Freddie
Company Specialist at Welcome to the Jungle
Insights
-17% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Jun 2024
$120m
SERIES C
Mar 2021
$60m
SERIES B
Total funding: $205m
Company benefits
- 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
Company HQ
The East Side, South San Francisco, CA
Leadership
Malinka Walaliyadde
(Co-Founder & CEO)Previously worked at Andreessen Horowitz (a16z), Counsyl and Corning Life Sciences. They have an Engineering degree from Cornell University.
Varun Ganapathi
(Co-Founder & CTO)They have successfully started two AI companies prior to AKASA. One was acquired by Google and the other by Udacity.
Andy Atwal
(Co-Founder & VP of Engineering)Prior to AKASA, they were the founding Software Engineer at Counsyl, a health technology company offering DNA screenings for various diseases.
Ben Beadle-Ryby
(Co-Founder)Previously, they were a Partner at the Advisory Board Company, where they oversaw revenue cycle consulting and technology.
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