AI/ML Job: Deep Learning Engineer


Deep Learning Engineer at Enlitic

Toronto, Canada 🇨🇦   (Posted Jun 6 2018)
About the company
Enlitic is a medical deep learning company. We leverage the collective knowledge of the medical community to derive insights from billions of clinical cases to enable more accurate diagnoses, faster. Our unique algorithms bring together medical images, text and other data sources to operationalize data assets. Our medical insights drive efficiencies in clinical operations and insurance billing, accelerate pharmaceutical research and drug trials, and increase diagnostic accuracy and speed to improve patient outcomes.

Job position

Job description
As one of the first 20 full-time team members, you will develop Enlitic’s next generation of machine learning algorithms for medical decision making. Our ideal candidate enjoys translating deep learning techniques into production code.

Skills & requirements
About You:

Your primary mission is to put machine learning algorithms into practice, while growing your own expertise in machine learning

Your excellent understanding of the foundations of deep learning allows you to explain CNNs to a four year old

You understand the value of sound, reproducible engineering practices, and believe that for machine learning to be successfully deployed in the real world, it must be surrounded and supported by the right production framework

You have strong coding skills, and can work in languages ranging from Python to C++ or Java, in a team development environment

You are familiar with scientific computing and systems using GPUs to parallelize operations

Once you are here you will:

Build maintainable pipelines for deep learning that can handle terabytes of data

Learn about machine learning, scalable high-bandwidth systems, and information security

Run experiments to test hypotheses with the team

Design and build novel systems to solve unique medical problems

Participate in a feedback loop to figure out the ways we can use deep learning to maximize the impact on patient care

Instructions how to apply
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