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    Machine Learning Engineer - San Francisco, United States - Health

    Health
    Health San Francisco, United States

    4 weeks ago

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    Description


    Health at Scale is the market leader in precision health digital health programs that offer smart, hyper-personalized insights to help individuals choose the best providers, treatments, care settings and lifestyle choices for their unique healthcare needs.

    Founded by leading machine learning and clinical faculty from MIT, Stanford, Harvard and the University of Michigan, we work with some of the largest payers, employers and providers in the U.S.

    to improve outcomes, costs, access, and equity for their members.

    Health at Scale operates some of the largest deployments of AI in healthcare to date, covering millions of lives in production settings.

    We have been recognized for our innovation and as one of the fastest growing private companies by Forbes, Fast Company, Inc 500, UCSF Digital Health, Becker's, TechCrunch, Bloomberg and MIT News.

    For more information, please visit our website.


    As a machine learning engineer at Health at Scale, you will work with an exceptional team of engineers, scientists, and clinicians to design, engineer, test, deploy and maintain machine intelligence platforms and applications for real-world production use.

    You will work closely to iterate and improve upon the machine intelligence technologies in each of our products.

    You will be the point person for translating machine learning innovations into impactful products with new customers and transforming leading-edge ideas into production-ready, real-time solutions that will serve millions of users.

    Responsibilities

    Design, engineer, test, deploy and maintain machine intelligence platforms and applications for real-world production use at scale
    Improve the accuracy, runtime, scalability and reliability of machine intelligence algorithms and software
    Develop and implement machine intelligence platform APIs for multiple use-cases
    Drive architecture of platform and application capabilities embedding machine intelligence
    Collaborate with machine learning scientists and data scientists to develop prototyped solutions and translate leading-edge ideas into production-ready systems
    Work with data engineers to ensure seamless interactions between data pipelines and machine learning pipelines in development and production environments

    Requirements

    BS, MS or PhD in Computer Science or related technical field
    2+ years of experience with machine learning and data science in academia or industry
    Strong understanding of the foundational concepts of machine learning and artificial intelligence
    Strong proficiency in Python (preferred), Java or C/C++
    Experience in cloud computing, parallel/distributed computing and workflow management
    Excellent communication skills

    Health at Scale is an equal opportunity employer and is committed to diversity in its hiring and business practices


    To all recruitment agencies:
    Health at Scale does not accept agency resumes. Please do not forward resumes to this job alias, company employees or any organization location. Health at Scale is not responsible for any fees related to unsolicited resumes.

    The starting base pay for this role is between $140,000-$210,000.

    The actual base pay is dependent upon many factors, such as relevant education, training, certifications, job-related skills, experience, qualifications, business needs, market demands and specific location.

    The total compensation package for this position may also include eligibility for annual discretionary bonus, equity and benefits (including medical, dental, vision).


    Note:
    The base pay range is subject to change and may be modified in the future.

    Health at Scale compensation, equity and benefit programs are subject to eligibility requirements and other terms of the applicable plan or program.

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