DRW is hiring a
Machine Learning Engineer, Web3 - Canada

Summary

The job description is for a Machine Learning Engineer position at DRW Montreal. The role involves designing and implementing scalable systems, optimizing training and inference performance of deep learning models, creating and maintaining feature pipelines, monitoring production models, optimizing models for deployment on different hardware configurations, building frameworks to promote scalable and reproducible research, driving projects and leading new initiatives, facilitating discussions on code implementation, testing, software architecture best practices, actively engaging with others on the team to resolve challenging design and coding issues, and collaborating with stakeholders from different departments. The qualifications required include a bachelor’s or master's degree in computer science, software engineering or equivalent, 3+ years of experience building software for machine learning systems, strong understanding of machine learning and deep learning concepts, excellent programming and scripting skills (Python and Go), experience with building, validating, deploying, monitoring, and updating production models, infrastructure and tooling for MLOps, strong problem-solving and analytical skills, excellent communication and collaboration skills, experience with machine learning frameworks such as TensorFlow, PyTorch, TensorRT, ONNX, experience with GPU programming using CUDA, OpenCL or similar libraries, experience with distributed systems and cloud computing (Kubernetes, Docker, GCP, AWS), multi-threaded programming, hardware/software interaction is an asset.

Requirements

• A bachelor’s or a master’s degree in computer science, software engineering or equivalent
• 3+ years of experience building software for machine learning systems
• Strong understanding of machine learning and deep learning concepts
• Excellent programming and scripting skills (we predominantly work in Python and Go)
• Experience with building, validating, deploying, monitoring, and updating production models
• Experience with infrastructure and tooling for MLOps
• Strong problem-solving and analytical skills
• Excellent communication and collaboration skills
• Experience with machine learning frameworks such as TensorFlow, PyTorch, TensorRT, ONNX
• Experience with GPU programming using CUDA, OpenCL or similar libraries
• Experience with one or more of the following is an asset: distributed systems and cloud computing (Kubernetes, Docker, GCP, AWS), multi-threaded programming, hardware/software interaction

Responsibilities

• Design and implement scalable and performant systems to serve machine learning models
• Optimize training and inference performance of deep learning models
• Create and maintain feature pipelines, feature stores, model stores
• Monitor production models and setup retraining infrastructure to improve performance
• Optimize models for deployment on different hardware configurations
• Build frameworks to promote scalable and reproducible research
• Drive projects and lead new initiatives
• Facilitate discussions on code implementation, testing, software architecture best practices
• Actively engage with others on the team to resolve challenging design and coding issues
• Collaborate with stakeholders from different departments

Benefits

• Recognized as one of Canada’s Best Employers for the past 8 years
• Continuous learning & development
• Industry leading benefits package and perks
• Focus on employee well-being and work-life balance
• Community initiatives, volunteer program and opportunities for giving back