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Hyperfine

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Hyperfine · Palo Alto, CA
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  • Hyperfine

    Senior AI Scientist

    Hyperfine · 🇺🇸 Palo Alto, CA · posted 2 months ago
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    About Hyperfine →

    The full posting

    About Us

    Hyperfine, Inc. (Nasdaq: HYPR) is the groundbreaking health technology company that has redefined brain imaging with the Swoop® system—the first FDA-cleared, portable, ultra-low-field, magnetic resonance brain imaging system capable of providing imaging at multiple points of care in a healthcare facility. Our mission is to revolutionize patient care globally through transformational, accessible, clinically relevant diagnostic imaging. Learn More

    About The Role

    Job Title: Senior AI Scientist

    Location: Palo Alto, CA (Hybrid, 3 days/week)

    The Senior AI Scientist is a talented and experienced Scientist with applied experience in Machine Learning who will innovate and expand our product capabilities. The goal of this role is to develop techniques that solve a wide range of challenging scientific and clinical problems in MRI aimed at improving patient outcomes. You will introduce new algorithms and machine learning models that solve difficult imaging tasks, make our models more accurate and robust, and introduce entirely new approaches.

    Key Responsibilities

    • Coordinate tasks and goals with other scientists, software engineers, and a clinical team to help develop a new suite of intelligent medical products.
    • Rapidly prototype deep learning models including, but not limited to, classification, detection, segmentation, reconstruction, super-resolution, and denoising; iterate on training models with fast turnaround time.
    • Design and develop new machine learning algorithms while keeping abreast of the latest advances across various labs and conferences.
    • Maintain and continuously improve our existing DL models, with new training data and modeling techniques.
    • Support software releases, and regulatory documentation.

    Knowledge, Skill & Abilities:

    • Ability to design new algorithms for practical problems on real-world datasets.
    • Ability to quickly learn new concepts and apply to research and development process in an iterative and incremental fashion.
    • Ability to work efficiently and clear roadblocks in timely manner.
    • Adaptability to fast-changing work environment.
    • Strong communication skills and proactiveness for working in a cross-functional collaborative environment.

    Required Education & Experience:

    • PhD in a relevant field, or MS (or equivalent) with 2+ years of applied experience.
    • Experience in Computer Vision, Medical Image Analysis, Machine Learning, or Deep Learning.
    • Experience working with Medical Images and Magnetic Resonance Images.
    • Software engineering experience in developing and maintaining systems using Python.
    • Programming experience in PyTorch and/or TensorFlow.

    Physical Demands:

    • This is a hybrid role based out of Hyperfine's office in Palo Alto, CA (minimum 3 days per week)
    • Occasional travel up to 10% of the time for conferences and/or team meetings in Hyperfine's office in Guilford, CT
    • Available nights, weekends, and holidays as business needs require.

    Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. Hyperfine is unable to sponsor or take over sponsorship now or in the future of any employment Visa.

    Compensation: The annual base salary for this position based out of Hyperfine's office in Palo Alto, CA is between $190,000 - $215,000. This position is also eligible for to participate in Hyperfine's corporate bonus and equity plans. Individual compensation packages are based on various factors unique to each candidate including skill set, relevant experience, qualifications, location, position level, and other job-related reasons.

    Agency Resumes: We do not accept resumes from recruitment agencies without a prior agreement in place. Any unsolicited resumes submitted by agencies will be considered the property of Hyperfine and will not be subject to any fees or charges if the candidate is hired.