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[Remote] Sr. Machine Learning Researcher

100% remote Flexible hours Hiring now

Note: The job is a remote job and is open to candidates in USA. AKASA is a leading provider of generative AI solutions for the healthcare revenue cycle, dedicated to transforming healthcare through AI. The Senior Machine Learning Researcher will play a crucial role in developing advanced AI solutions, collaborating with a team to enhance operational workflows and improve patient care through innovative machine learning models.

Responsibilities

  • 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

  • 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
  • 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

Benefits

  • 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

Company Overview

  • AKASA is rapidly becoming the GenAI partner of choice for leading health systems, with recent national recognition of our Cleveland Clinic deployment as “one of the most comprehensive real-world uses of GenAI in healthcare finance to date.” Across customers, AKASA now delivers an average of $3.1M in additional revenue and 4,270 additional quality indicators per 10,000 discharges, demonstrating consistent, measurable impact. It was founded in 2019, and is headquartered in South San Francisco, CA, US, with a workforce of 51-200 employees. Its website is https://www.akasa.com.

Company H1B Sponsorship

  • AKASA has a track record of offering H1B sponsorships, with 5 in 2024, 1 in 2023, 8 in 2022, 2 in 2021. Please note that this does not guarantee sponsorship for this specific role.

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