Senior Machine Learning Engineer

Senior Machine Learning Engineer

Remote/Telecommute JobREMOTE / Toronto, Ontario, Canada  - Permanent
This job allows you to work remotely 

Job Description

Our client is on a mission to build an actionable, interoperable regulatory-grade data layer. They're 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 along with strategic angels across North America - who have previously backed several multi-billion-dollar companies that have gone onto IPO or exit.

They seeking motivated and driven Machine Learning Engineer(s) to work on the core product - a backend expert able to unify data, and build systems that scale from both an operational and an organizational perspective.

As a Machine Learning Engineer you will:

- Design, develop, test, and maintain the data processing and ETL process from multiple, disparate structured/unstructured data sources (e.g. HL7 interfaces, medical ontologies, human/crowdsourced 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
- Develop and implement novel data-acquisition and labeling systems (e.g. active learning, crowdsourcing)

Must Have Skills:

We are looking for people who are rockstars and have:

- 3+ (preferably 5+) years in designing, implementing, and maintaining data processing and ETL pipelines on multiple, disparate sources of data, preferably with large-scale data processing pipeline (like Hadoop or Spark)
- 3+ (preferably 5+) years in designing, implementing, testing, and maintaining machine learning pipelines
- Excitement 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
- Expert experience architecting, writing, optimizing, & debugging software applications, in modern stacks with a focus on building scalable ML

Nice to Have Skills:

Bonus points if you have experience with:

- Industry or academic experience working on various ML problems (especially NLP)
- Experience with deep learning frameworks such as tensorflow and Pytorch
- Developing and improving core NLP algorithms not just grabbing things off the shelf
- Experience with managing large-scale data labelling and acquisition, through tools such as through Amazon Turk or DeepDive.


Starting: ASAP

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