Love sensing? Love personalized health? QMedic is hiring!

Treatment vs PreventionDo you daydream about using sensory data to personalize healthcare?  Well, you’re not alone! 

QMedic is introducing the next wave in personalized medicine: passive sensing to predict behavior and help remote caregivers coordinate care in the home.  If you share our vision for preventative healthcare, have a passion to transform raw sensory data into meaningful outcomes, and want to push the boundaries in signal processing, this is the opportunity for you.

QMedic is the recipient of an SBIR contract from the NIH/National Cancer Institute, was a finalist for AARP's startup award, and was selected from over 2,500 startups as a Big Data and High Performance Computing finalist for the Amazon Web Services Global Startup Challenge. Most recently, QMedic was invited to TEDMED as one of 50 top innovators disrupting health and medicine. 

The opportunities for you to make an impact and grow at QMedic are limitless.  As Lead Machine Learning Engineer, you will be responsible for developing and implementing power-efficient cloud-based algorithms to process raw data from wearable motion and location sensors.  In addition, you will be able to analyze patient- and third-party reported data to contextualize individual and group behavior.  Above all, your work will contribute directly to helping caregivers intervene against the risk factors and behaviors associated with health decline and chronic disease.

If re-inventing health and wellness sounds like your cup of Java, we invite you to join our team.

Required Experience:

  • Minimum 3-5 years of experience in C, C++, Python, and Java
  • Solid understanding and hands-on experience with advanced machine learning techniques such as hidden Markov models, decision trees, Bayesian networks, particle filtering, etc.
  • Demonstrated proficiency in mathematical/statistical programming using tools such as R, MatLab, Weka, etc.
  • Masters Degree and above in Computer Science or related field
  • Experience in wearable computing and mobile development (e.g. MEM sensors, iPhone, Android) is desirable but not required.


  • $100K and up, commensurate with experience
  • Equity negotiable and subject to vesting
  • Comprehensive family health insurance (i.e. medical, dental, vision) provided

If interested, please send a brief statement of interest, resume, and at least 2 references to jobs at qmedichealth dot com  (Subject Line: "Machine Learning Engineer, ATTN: Fahd Albinali").  In place of a resume, you may share a link to your LinkedIn or StackOverflow/Careers 2.0 profile.

Interested in reading more posts from QMedic - Read our last post "QMedic at Mobile Monday".