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Senior Machine Learning Engineer


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We are looking for a Senior Machine Learning Engineer for Semantic Health, a Toronto-based healthcare technology company leveraging proprietary artificial intelligence to help hospitals improve their medical coding, auditing, and CDI processes.

The Senior Machine Learning Engineer will be working on the core product – as ML expert you will research, design, and implement machine learning models, data pre-processing, and think out of the box solutions for tough problems.

In this role, you will:

  • Design, develop, test, and maintain the data processing and ETL pipelines from multiple, disparate structured/unstructured data sources (e.g. HL7 interfaces, medical ontologies, human/crowd sourced inputs)

  • Design and implement and maintain the core data models and databases in a scalable and fault-tolerant manner, and build performant interfaces to this data

  • Design and build large-scale, cloud or on-premise machine learning pipeline (processing, training, inference, monitoring) in a replicable, well documented, scalable, and highly performant manner

  • Design and build large-scale, cloud or on-premise machine learning platform components (feature store, hosting services, online/offline experiment services, deployment services) in a replicable, well-documented, scalable, and highly performant manner

  • Develop and implement novel data-acquisition and labelling systems (e.g. active learning, crowdsourcing)

  • Participate in your team's business hours on-call rotation, triaging and addressing production issues as they arise.

The ideal candidate will:

  • Have experience in designing, implementing, and maintaining data processing and ETL pipelines on multiple, disparate sources of data, preferably with both big data and small data

  • Be experienced in designing, implementing, testing, and maintaining machine learning pipelines and platforms

  • Have the experience in architecting, writing, optimizing, & debugging software applications, in modern Python stacks with a focus on building scalable ML

  • Be excited about learning how to build and support machine learning pipelines that scale not just computationally, but in ways that are flexible, iterative, and geared for collaboration

Skills and experiences that will give you an added advantage:

  • Industry or academic experience working on various ML problems (especially NLP)

  • Knowledge of and experience with deep learning frameworks such as Tensorflow and Pytorch

  • Demonstrated experience in developing and improving novel NLP algorithms

  • Experience with managing large-scale data labelling and acquisition, through tools such as through Amazon Turk or DeepDive.

About the employer:

Semantic Health is on a mission to build an actionable, interoperable regulatory grade data layer starting by improving the manual and error prone medical coding and auditing processes at major hospital providers in North America.

They are a team of entrepreneurs, doctors, engineers, and researchers from Harvard, University of Toronto, Vector Institute, Snowflake, and numerous start-ups. They are backed by some of the leading investors globally including Data Collective (SF), Liquid 2 (SF), Union Ventures (Toronto), and strategic angels across North America - that have previously backed several multi-billion-dollar companies who have gone onto IPO or exit.



Other benefits:

PKR 250,000 - 350,000 (Negotiable for outstanding candidates)

  • Canadian immigration after 18-24 months with the company

  • Bi-weekly sessions with top engineers from Silicon Valley on topics of interest

  • Access to seed funding for our engineers' ideas after they have spent 3 years with us.

  • The opportunity to work with an A-Team 

  • Annual bonuses and leave

  • ESOP

  • Health Insurance

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