Machine Learning Specialist

Canada·Montréalmid

Learning & Development SpecialistPeople

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Quick Summary

Key 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,

Requirements Summary

A bachelor’s or a master’s degree in computer science,

Technical Tools

Learning & Development SpecialistPeople

Responsibilities

~1 min read

→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

Requirements

~1 min read

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
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 optimizing inference performance (quantization, profiling, kernel/runtime tuning, serving engines)
Experience with one or more of the following is an asset: distributed systems, multi-threaded programming, hardware/software interaction