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Machine Learning Engineer / Scientist
Q Bio
Open to Remote Hybrid - United States /
Q Bio is building technology for the Physical of the Future that measures more, faster and cheaper about the human body, to enable proactive primary care for all. We're revolutionizing primary care with the first clinical digital twin platform, powered by breakthrough whole-body scanning technology, that highlights the most important changes in a person’s physiology for sharing with physicians and specialists anywhere in the world. 

Join us!

Q Bio’s clinical digital twin platform, Gemini, is the first to capture and monitor comprehensive baseline patient health in a scalable virtual model. The Gemini Dashboard highlights the most important chemical and anatomical changes in an individual weighted by an individual’s lifestyle, genetic and medical history, that can be securely shared with physicians and specialists all over the world.

Gemini is powered by the fastest, most accessible, whole body scanner developed: the Mark I. Self-driving and optimized for primary care, the Mark I can complete a whole-body scan in 15 minutes or less in an open space, without radiation, breath holds, or claustrophobia. Patient comfort is maximized with the option to sit, stand, or lie down, and real-time telemetry is displayed throughout.

Why should you consider a career with Q Bio? 

We dream big. Our team is aligned and excited about the opportunity to save lives and understand the human body like never before. We know how critical empowering and supportive leadership is, both to our excellence as a company, and for our team experience as a whole, and our leadership team will empower and support career growth. We’re a team of engineers, scientists, and operators who come from a diverse background of disciplines and experiences. We value teamwork, growth, determination and persistence, commitment to collaboration, and a reliance on staying nimble while keeping the big picture in mind. 

Team Structure

The Radiomics Engineering Team is divided into four smaller teams: Image Acquisition/Pulse Sequence Design, Image Reconstruction, Image Post-processing, and Hardware Engineering. While each team functions independently, we value  cross-pollination of ideas, open discussion, and sharing of knowledge. As a company, we all work towards the primary goal of developing a reproducible, non-invasive, and  high-speed whole body exam. 

We’re hiring a ML applied scientist and looking to grow our team with talented individuals with expertise in AI/ML particularly in the areas of deep learning, segmentation, classification and biomedical image analysis. This is a hands-on position where you will be empowered to be creative and bold, to solve novel R&D problems and have the potential to directly impact the lives of our members.

Role Responsibilities

    • Explore and implement novel algorithms for medical image analysis.
    • Analyze and preprocess imaging data for model training and validation.
    • Plan and execute ML experiments, and set milestones and timelines to achieve objectives.
    • Write production level code and deploy ML-powered applications to obtain valuable insight from real life data.
    • This is a hands-on position where you will be empowered to be creative and bold, to solve novel R&D problems and have the potential to directly impact the lives of our members.

Candidate Requirements

    • PhD in Electrical Engineering, Biomedical Engineering, or equivalent research experience 
    • At least 3 years of experience in ML model development, particularly in medical imaging utilizing MR or CT data. 
    • Strong background in developing deep learning, computer vision and machine learning algorithms in Python and working with DL libraries such as TensorFlow and  PyTorch, Keras,  Caffe.
    • Proven experience with developing models for segmentation, classification and detection.
    • You thrive in fast-moving environments where you work with cross-functional stakeholders including executives, scientists, clinicians, and engineers

Benefits offered at Q Bio:

    • Competitive salary and equity in a well-funded, early stage startup
    • Healthcare, vision, and dental coverage for you and your dependents
    • Progressive paid family leave and sick leave plans
    • Complimentary annual Q Exam
    • Personalized catered meals every day
    • Opportunity to work on a highly interdisciplinary team and become an expert in computational biology, biotechnology, and the cutting edge of digital health tech while getting hands-on experience with it!
We are mission first, passionate about building things, and passionate about learning. We're looking for people that bring those same values, that can propel us along our mission, that can build great things, and where we can learn from each other and grow along the way.

In the San Francisco Bay Area, the standard pay range for this role is $160,000-$180,000 annualized. This pay range is for the San Francisco Bay Area and is not applicable to locations outside of this location or for remote roles. Actual amounts will vary depending on experience, performance, and work location. In addition to a competitive base salary, we offer significant equity and an employee-friendly stock option plan. Employees will also be eligible to participate in benefits plans available to other similarly situated employees subject to any eligibility requirements imposed by such plans.

Q Bio was founded in 2015 by serial entrepreneur Jeffrey Kaditz, Dr. Michael Snyder, Chair of Genetics and Director of Personalized Medicine at Stanford University, and Dr. Garry Choy, physician, radiologist, and former Chief Medical Information Officer at Mass General Hospital. Q Bio has raised over $80M from world class investors including Andreessen Horowitz, Kaiser Foundation Hospitals, Khosla Ventures, Founders Fund, SciFi VC, and many more.

Q Bio is an Equal Opportunity Employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Full-time
Mid Level