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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 multiple wins of international machine learning competitions, including the prestigious ACM RecSys Challenge in (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), Kaggle: RSNA Pneumonia Detection Challenge (4th place in 2018) and the Stanford Question Answering Dataset (2nd place in 2019).
About the role:
Robust, trustworthy, and efficient data system is crucial for developing and deploying ML models in production. In addition to handling the complexity of massive data sources, ML data system also needs to provide strong support for data science specific tasks.
Data Engineering team at Layer 6 focuses on building robust data pipelines, machine learning focused data validation system, and centralized asset (data, features, and models) management system.
We aim to provide industry-leading solutions to our machine learning engineers while operating a machine learning platform at scale.
We are looking for experienced data engineers and problem solvers who have worked with tight deadlines and challenging tasks. The ideal candidate will be passionate about data-centric solutions and machine learning systems. The candidate should be able to design and implement components of data system and lead by example. The candidate should also interact with machine learning scientists, the infrastructure team and data sources team to develop systems that will satisfy the needs of machine learning projects.
What are your responsibilities?
- Contribute to the planning and execution of data pipelines for various machine learning projects
- Design, implement, and maintain data pipelines with complex data transformations
- Implement key components of data validation and management system
- Perform profiling and troubleshooting of the existing data-centric solutions
- Automate existing manual steps and optimize the overall data transformation processes
At TD, we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. We are dedicated to building a workforce that reflects the diversity of our customers and communities in which we live and serve. If you require an accommodation for the recruitment/interview process (including alternate formats of materials, or accessible meeting rooms or other accommodation), please let us know and we will work with you to meet your needs.