Senior Machine Learning Software Engineer, Medical Devices Software

South San Francisco, CA

Full Time Senior-level / Expert
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Verily

Verily is focused on using technology to better understand health, as well as prevent, detect, and manage disease. Our mission is to bring together technology and life sciences to uncover new truths about health and disease.

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Verily is an Alphabet company combining a data-driven, people-first approach to bring the promise of precision health to everyone, every day.

Our team combines expertise in healthcare, data science and technology to improve the health and well-being of our communities. We are developing the infrastructure and solutions to harness the profusion of health information for good. Our data-driven solutions span three primary areas: research, care and innovation. Programs include Project Baseline - our research initiative to increase participation and evidence generation in clinical research; Onduo - our personalized virtual care platform, which includes connected tools, lifestyle coaching and clinical support; and Debug - our effort to reduce the threat of mosquito-borne diseases by combining machine learning with sterile insect technique. We’re also actively working to combat the spread of COVID-19 through new programs like Healthy at Work

Description

The Medical Devices Software team is building a revolutionary imaging device service platform. This platform uses various kinds of cameras in order to close medical gaps. The imaging system mixes commodity electronics and computer vision and machine learning solutions. As a Machine Learning Pipeline Software Engineer on both our backend/cloud and device software teams, you’ll be working in collaboration with Google/Verily teams to help develop and productionize models and tools for disease diagnosis and treatment determination. Our team supports multiple Verily projects, so this role provides an opportunity to gain exposure to a variety of unique products.

Responsibilities

  • Be part of the product teams translating advanced ML research into innovative and applied on-device ML Software as Medical Device (SaMD) products, with GPU and TPU technologies.
  • Actively participate in scoping requirements, ML pipeline design and development, (on-device) ML model development, evaluation and validation.
  • Work as an independent ML software engineer through the entire cycle of SaMD productionisation under regulatory and quality management processes. 
  • Work closely with data science, UX, hardware, application and software engineers to create highly integrated novel products.
  • Collaborate with teammates across the Medical Devices Software organization to advance our development practices.

Qualifications

Minimum qualifications:

  • BS degree in Computer Science, Computer Engineering or related technical field and equivalent practical experience with 3+ years of software development experience.
  • 3+ years of machine learning pipeline experience, familiarity with machine learning model development lifecycle, including study design, data collection and annotation, model development, model validation and rigorous statistical analysis.
  • Experience with programming and scientific computation using Tensorflow/PyTorch and Python.
  • Willingness to learn/grow, and respectfulness that allows colleagues to do the same.

Preferred qualifications:

  • Familiarity with GPU-based technologies like CUDA, TensorRT, OpenCV, or ONNX, is a plus.
  • Familiarity with building and deploying computer vision and on-device machine learning on bespoke devices. Experience of interfacing with cloud-based computer vision solutions is a plus.
  • Experience with cloud deployment technologies: Docker, Kubernetes, Google Cloud Platform or other cloud providers.
  • Experience with IoT product solutions is a plus.

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Tags: Computer Science Computer Vision CUDA Docker Engineering GCP Google Cloud GPU Kubernetes Machine Learning ONNX OpenCV Python PyTorch Research TensorFlow TensorRT UX

Region: North America
Country: United States
Job stats:  9  3  0
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