Website Clairity, Inc.
Better Science Leads to Better Care
Clairity is seeking an 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 Principal 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 Principal ML engineer will work closely with research partners, data partners, data engineers, ML engineers, MLOps engineers, and software engineers with the goal of developing commercial-grade ML solutions.
We are seeking a Principal ML engineer with a strong background in the development and optimization of machine learning methods in medical imaging. He or she will have a strong experience of ML best development practices. The ideal candidate is a team player, highly motivated self-starter, with an innovative mindset and demonstrated ownership 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 ~$9 million in funding from investors. The location of the position is flexible within the United States, with the ability to work remotely from home.
– Act as technical lead for all Company’s ML modeling and ML research activities
– Manage Company’s ML research data pipeline
– Conduct validation of research prototypes in collaboration with academic and clinical partners
– Provide scientific assistance for regulatory submissions
– Write publications in peer-reviewed literature and generate Intellectual Property materials
– 5+ years of software development in a corporate setting
– 5+ years of developing Computer Vision ML solutions for image analysis, image segmentation and image classification tasks
– Strong track record of publications and innovations
– Experience developing image processing algorithms for image analysis, image segmentation and classification
– Strong mathematical and statistical background
– Experience of supporting scientific regulatory submissions
– Familiarity with ML production pipelines in AWS
– Practical experience in the following areas:
– ML architectures: CNN, RNN, Vision Transformers
– ML toolkits: TensorFlow, Keras, scikit-learn
– ML services: SageMaker Pipelines, MLflow
– Serverless Computing: Docker containers, AWS Lambda, AWS Fargate
– Pipeline orchestration: AWS Step Functions, Kubeflow Pipelines
– Application exchange: REST API, JSON
– Programming languages: Python
– Software tools: Git, Gitlab, GitHub, JIRA, Confluence
Masters in Computer Science, Electrical Engineering or related discipline or equivalent industry experience. Ph.D. degree in Computer Science or Engineering preferred
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