About Us: Artera is an AI startup that develops medical artificial intelligence tests to personalize therapy for cancer patients. Artera is on a mission to personalize medical decisions for patients and physicians on a global scale. As a Machine Learning Engineer at Artera, you’ll work on the AI Platform team. You’ll be focused on enabling Artera’s model developers to produce clinically useful and/or scientifically impactful AI models across a wide range of cancer indications. You’ll work closely with model developers, biostatisticians, and infrastructure engineers to streamline and automate model development workflows,
Essential Responsibilities:
Build and own tools and libraries that accelerate Artera’s ability to develop, launch, and monitor AI products.
Contribute to an evolving data platform utilized by Biostats and machine learning engineers to index, curate, and version all of Artera’s rapidly growing data.
Work with model developers to optimize the efficiency and utilization of large-scale, foundation model, and downstream model training runs.
Optimize Artera’s ability to store terabytes of digital pathology data efficiently for model development.
Experience Requirements:
5+ years of industry experience using Python
3+ years of industry experience using one of PyTorch, TensorFlow, or JAX
3+ years of industry experience building with AWS, Docker, and Kubernetes
Desired:
Experience using Terraform, SqlAlchemy
Experience using ML orchestration frameworks such as Kubeflow, Metaflow, MLFlow, Flyte, Dagster, Argo Workflow or Prefect
Experience maintaining infrastructure for machine learning training and production inference
Experience designing and developing internal tools to be used by non-technical teams
Equal Employee Opportunity: At Artera, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients and physicians. As an equal opportunity employer, we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.
