ML DevOps Engineer

Work Location:

Canada

Hours:

37.5

Line of Business:

Data & Analytics

Pay Details:

We’re committed to providing fair and equitable compensation to all our colleagues. As a candidate, we encourage you to have an open dialogue with a member of our HR Team and ask compensation related questions, including pay details for this role.

Job Description:

Layer 6 is a leading Canadian machine learning applied research company, a fully owned subsidiary of TD Bank Group. Layer 6 develops advanced machine learning and deep learning systems that have the power to uplift large populations while advancing the field of artificial intelligence. Our research is supported by access to massive datasets, close collaboration with world renowned academic faculty, and a uniquely scalable machine learning platform. 

 

Our technical capabilities have been publicly recognized through a number of wins in various international machine learning competitions, including the prestigious ACM RecSys Challenge (the only repeat winner in 2017 and 2018 and runner-up in 2019), Google’s Landmark Retrieval Challenge (2nd place in 2018, 3rd place in 2019), the Stanford Question Answering Dataset (2nd place in 2019), 3rd YouTube-8M Video Understanding Challenge (winner in 2019) and Open Images 2019 - Visual Relationship (winner in 2019). 

 

Job Description: 

 

We are looking for experienced Machine Learning Systems Engineers who have worked under tight deadlines and on challenging tasks. The ideal candidate is a strong coder with solid data engineering experience. They should also have expertise in machine learning, system design and DevOps. 

 

You will: 

• Design and implement components of data and model delivery system and lead by example.  

• Interact with machine learning scientists, the infrastructure team and data sources team to develop systems that will satisfy the needs of machine learning projects 

• Implement complex data-centric solutions, including extremely complex and large data set verification, transformation and feature generation, to ensure continuous high-quality input for the model development 

• Build model delivery systems, including inference pipeline, automatic model validation reports generation, automatic model performance monitoring and model retraining, to ensure fast model productionization and reliable production system 

• Maintain the model in production and ensure the data/model related knowledge continuation within Layer 6 

• Develops and maintains technical solutions that adhere to engineering and architectural design principles while meeting business requirements 

• Provides technical expertise with a focus on efficiency, reliability, scalability, and security; includes planning, evaluating, recommending, designing, operationalizing, and supporting solutions in compliance with enterprise and industry standards 

 

Job Requirements: 

 

Required Technical Qualifications 

• BSc+ in Computer Science, Math, Physics, or similar 

• 2+ years of extensive programming experience, at least 1 year in building production data systems 

• 1+ year experience of building machine learning production system 

• Strong experience with major Big Data technologies and frameworks including but not limited to Hadoop, MapReduce, Spark, Cassandra, Kafka, Elasticsearch  

• Good knowledge of Machine Learning and Deep Learning 

• Practical expertise in performance tuning, bottleneck problems analysis, and troubleshooting