ML Ops Engineer

GenHealth.ai seeks an exceptional ML Ops Engineer to develop and deploy generative AI models in healthcare. Join our passionate team to improve patient outcomes and reduce healthcare costs. Apply today to make a significant impact!

About the ML Ops Engineer Role at GenHealth

GenHealth.ai is transforming the way healthcare works, and we are looking for an exceptional ML Ops Engineer to join our team. As a member of our team, you will be at the forefront of generative AI in healthcare, making a significant impact on the lives of patients around the world.

The ML Ops Engineer role at GenHealth will develop and deploy state-of-the-art generative AI models in healthcare. You will work with a team of passionate and talented individuals with a track record of successful startups who are dedicated to improving patient outcomes and reducing healthcare costs.

Responsibilities

  • Hands on keyboard development of cutting-edge generative AI models at all layers of the stack.
  • Scale Transformer Neural Network training, testing, and evaluation for models that run on over 100M patient records.
  • Work with a team of engineers and data scientists to develop and deploy AI models applicable to diverse and domain-specific healthcare use-cases
  • Stay up-to-date with the latest developments in AI and healthcare technology

Requirements

  • Strong experience at all levels of the stack, from the systems/OS level and physical infrastructure, to high-level business logic.
  • Experience with modern data engineering tooling at scale likw DBT, Apache Arrow, Polars, DuckDB, Dagster, Ray.
  • Experience working with datasets in the 10s of TBs or larger. Our nodes may see multiple PBs of traffic per day
  • Strong background in AI and Machine Learning with experience in developing and deploying AI models in production
  • Experience with Transformer Neural Network training and testing in production for very large models
  • Experience with MLOps and automating deployment, testing, and drift detection
  • Well versed and much experience with GNU/Linux.
  • Deep Python experience, should understand the differences between different python releases, be comfortable and be able to explain the different packaging systems. Has used and packaged PyTorch code in production.
  • Experience with containerization technologies like Docker or Kubernetes
  • Deft with shell, CI/CD, and cloud environments like AWS
  • Passion for making a significant impact on the healthcare industry using AI

Extra Credit

  • Experience managing H100 or A100 GPUs at the OS and physical level.
  • Experience working with EHR, FHIR, and/or Claims data
  • Experience working with and debugging CUDA
  • Strong Experience in C, C++, or Rust. Familiar with tools like gdb and strace.
  • Deep GNU/Linux experience. NixOS, Debian, Arch. Knows how to patch a kernel. Can build a kernel module without distro-managed tools.
  • Passion for open source software.

Compensation and Benefits

The salary for this role is $150,000 – $250,000. In addition to salary, total compensation includes the following

  • Healthcare, dental, and vision insurance for your entire family
  • Equity (stock options) valued between $50,000 - $150,000.
  • Unlimited vacation and 15+ company holidays per year
  • Work directly with the founders

At GenHealth.ai, we are transforming the healthcare industry with cutting-edge Generative AI technology. As an ML Ops Engineer at our company, you will work on projects that will improve the lives of millions of patients around the world. If you are passionate about using AI to make a significant impact on the healthcare industry and have experience in scaling Transformer Neural Network in production, we encourage you to apply today!

We take pride in our focus on equity. We are a proud equal opportunity employer and encourage individuals from all backgrounds and identities to apply for this position. We believe in fostering an inclusive and diverse workplace and are committed to supporting our employees’ professional growth and development.

Apply Now