Product Machine Learning Engineering Manager at Sophia Genetics

| Greater Boston Area | Remote
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Would you like to lead a Product Machine Learning team charged with developing scalable models and actionable insights within our game changing computational platform used to deliver genomic, radiomic, and clinical data analysis to over 1000 healthcare institutions and over 500,000 cancer and rare genetic disease patients worldwide? Join our growing distributed team and use your exceptional technical and leadership skills to help us deliver on our mission of democratizing Data-Driven Medicine.

In order to augment our leadership team we are looking for a Product ML Engineering Manager to join our team in the US, working from home office, with occasional face-to-face meetings as needed.

As a Product ML Manager, you will report directly to the Vice President of Engineering and will lead our product machine learning efforts in a number of key areas of our platform.

Your principal responsibility will be to build and lead an all-star Product ML team, consisting of ML Engineers and Analysts focusing on building practical models and generating product insights within SOPHiA DDM, our flagship software product, used to perform large-scale multi-modal analysis of patient data and deliver data-driven insights to hundreds of thousands of patients worldwide.

Our platform is a one-of-a-kind globally distributed information system that brings together hospitals and labs to provide data ingestion and processing, analysis and modeling, reporting and intelligence, distribution and sharing of a multitude of complex sources of structured and unstructured data, including genomics, imaging, and clinical data, delivered as a multi-tenant SaaS platform on the cloud.

As part of your team’s mission you will develop systems for comprehensively collecting, and analysing a wide variety of product usage data and will develop key metrics to help our product organization turn these into actionable insights. You will develop automated systems for anomaly detection and response. You will develop models and machine learning algorithms to help us make better use of our primary data sets, including genomic, imaging, and clinical data, and help us develop innovative ways to integrate and process this data with higher quality, lower turnaround time, and at a lower cost.

Some travel between various SOPHiA offices and customer sites may be required (up to 10%).

Requirements

You are a senior ML Engineering leader who has extensive experience working in distributed organizations as part of the technology team. You have a track record of successfully developing scalable ML models and turning these into actionable product insights. You have extensive technical skills and are up to date with the latest developments in the ML field being proficient in supervised, unsupervised, and reinforcement learning methods. You have mastery of all areas of machine learning and quantitative analysis including hypothesis generation, model selection, model development, training and validation, inference, scalability and production deployment of large-scale models, exploratory analysis, and data visualization. You are quantitative and systematic in all areas of your work. You are judicious in developing and applying the simplest statistical methods that will get the job done, instead of reaching for fashionable and unnecessarily complex. You understand how to build quality and drive continuous improvement. You are able to communicate effectively using data at all levels of the organization. You are passionate about making a difference in the lives of patients.

  • Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a similar field, or equivalent professional experience
  • Extremely solid fundamentals in statistical learning methods
  • 7 years’ experience in ML engineering
  • 2 years’ experience as a direct people manager
  • Deep experience with multiple ML stacks, such as Keras, Pytorch, Tensorflow, scikit-learn
  • Expertise in exploratory analysis and data visualization
  • Expertise in building and supporting large-scale production ML models through multiple iterations.
  • Well-rounded software engineering experience, including a variety of technology ecosystems such as Python, Java, and C++.
  • Experience with genomics, digital image analysis, and clinical data analysis is an asset
  • Excellent interpersonal and communication skills
  • Knowledge of software engineering best practices (Agile, Continuous Value Delivery, CI/CD, DevOps, NoOps, PaaS, IaaS, LEAN software, Service Oriented Architecture, cloud computing)

Benefits

  • A flexible, friendly and international working environment with a collaborative atmosphere
  • An exciting company mission that brings together science and technology to directly impact the lives of patients with life threatening illness.
  • A fast-growing company with plenty of opportunity for personal growth and development
  • A hard technical challenge to solve with exciting modern technology - cloud computing, Big Data, DevOps, machine learning

Location: HOME OFFICE (Massachusetts and the surrounding states, 2-3h from Boston)

Start: ASAP (or as agreed)

Contract type: permanent full-time

Application process

If you think you fit this position, please send a CV and a cover letter. Please note that incomplete applications will not be considered.

After an initial screening process, candidates will be invited for remote interviews. Selected candidates will then be invited for personal interviews.

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Technology we use

  • Engineering
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Location

185 Dartmouth Street, Suite 502, Boston, MA 02116
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