Website Clairity

Better Science Leads to Better Care

Clairity is seeking an experienced Machine Learning (ML) Engineer to help advance our mission of revolutionizing healthcare. With an initial focus on breast cancer screening, we will build mammography-based machine learning (ML) solutions that accurately predict the risk of cancer, personalize the plan of care, cultivate trust, and save lives. We want to expand our team with someone who shares our appreciation for the rapidly evolving power of big data and machine learning, and who enjoys bringing to production state-of-the-art algorithms to solve novel real-world healthcare problems.

The ML engineer will be responsible for the prototyping of state-of-the-art ML solutions as well as the management of Company’s ML research data pipeline. He or she will also assist in the collection, cleaning, and organization of large databases from heterogeneous data. The ML engineer will work closely with research partners, data partners, data engineers, ML engineers, and software engineers with the goal of developing commercial-grade ML solutions.

The ideal candidate will have a strong experience in the development, optimization, and production of machine learning models in medical imaging. He or she will have a strong understanding of ML best development practices, and a prior experience of data engineering work for ML-based products. The ideal candidate is a team player, highly motivated self-starter, detailed-oriented with demonstrated ownership, accountability, and commitment to high quality deliverables.

Founded in 2020 by Santé Ventures and Dr. Connie Lehman, the Head of Breast Imaging at Massachusetts General Hospital, Clairity is located in Austin, TX and has raised ~$29 million to date in funding from investors. The location of the position is flexible within the United States, with the ability to work remotely from home.

Primary Responsibilities

  • Develop state-of-the-art computer vision models for breast cancer risk prediction.
  • Manage Company’s ML research data pipeline.
  • Assist team with data collection and infrastructure work.
  • Conduct model validation in collaboration with academic and clinical partners.
  • Provide scientific assistance for regulatory submissions.
  • Write publications in peer-reviewed literature and generate Intellectual Property materials.

Requirements (Essential)

  • 5+ years of ML development work in a corporate setting
  • 5+ years of developing Computer Vision ML models (deep learning and image processing) for image analysis, image segmentation and image classification tasks
  • Strong track record of publications and innovations in ML and/or Software as a Medical Device using ML
  • Practical experience of the following technologies:ML architectures: CNN, Vision Transformers
    – ML toolkits: TensorFlow, Keras, scikit-learn
    – Cloud: ML Managed services, preferably on AWS
    – ML: TensorFlow, SageMaker Pipelines, TensorFlow Serving
    – Databases: data warehouse and relational databases
    – Deployment: Gitlab, Docker containers, AWS CodePipeline
    – Pipeline orchestration: AWS Step Functions, Airflow, MLFlow
    – Application exchange: REST API, JSON
    – Programming languages: Python
    – Software tools: Git, GitHub, JIRA, Confluence

Requirements (Preferred)

  • Corporate experience in the regulated medical imaging or healthcare IT industry
  • Prior experience of implementing orchestration and data management workflow solutions
  • Understanding of Software Development Life Cycle for software medical devices
  • Experience in version control of ML models (code, data, config, model) and model registries


  • Undergraduate degree in Computer Science or Engineering. Master’s degree or PhD in computer science or engineering preferred.

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