Machine Learning Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer based in Canada.

This role is focused on building and scaling next-generation intelligent systems that power complex, data-driven logistics and supply chain platforms. You will work on developing and deploying deep learning and reinforcement learning models that operate at scale in production environments. The position sits within a highly technical research and engineering team, collaborating closely with data scientists, software engineers, and product teams. You will play a key role in transforming advanced research into real-world, production-ready systems with measurable business impact. The environment is fast-moving and innovation-driven, requiring strong problem-solving skills and a deep understanding of machine learning systems. You will also contribute to improving model performance, reliability, and efficiency across distributed infrastructures.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer based in Canada.

This role is focused on building and scaling next-generation intelligent systems that power complex, data-driven logistics and supply chain platforms. You will work on developing and deploying deep learning and reinforcement learning models that operate at scale in production environments. The position sits within a highly technical research and engineering team, collaborating closely with data scientists, software engineers, and product teams. You will play a key role in transforming advanced research into real-world, production-ready systems with measurable business impact. The environment is fast-moving and innovation-driven, requiring strong problem-solving skills and a deep understanding of machine learning systems. You will also contribute to improving model performance, reliability, and efficiency across distributed infrastructures.

Accountabilities:

• Design, build, and scale production-grade machine learning systems for deep learning and reinforcement learning models across distributed environments.
• Develop and optimize model inference performance using advanced techniques such as quantization, pruning, and distillation to improve efficiency and scalability.
• Build and maintain robust ML pipelines for training, deployment, monitoring, and continuous improvement of models in production.
• Leverage GPU computing and distributed systems to accelerate training and inference workloads across cloud infrastructure.
• Collaborate closely with data scientists and engineers to translate research prototypes into reliable, scalable production systems.
• Monitor model performance in production and implement improvements to ensure accuracy, stability, and efficiency over time.
• Stay current with emerging research in deep learning and reinforcement learning and integrate relevant advancements into production systems.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field.
• 3+ years of experience in machine learning engineering or software engineering roles focused on ML systems.
• Strong programming skills in Python, with additional experience in C++ or Java considered an asset.
• Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.
• Experience working with GPU acceleration technologies such as CUDA or similar computing frameworks.
• Strong knowledge of distributed systems and cloud platforms such as Kubernetes, Docker, AWS, or Google Cloud Platform.
• Experience building and deploying machine learning models in production environments, including APIs and scalable inference systems.
• Strong communication and collaboration skills, with the ability to work effectively across multidisciplinary teams.
• Nice to have: experience with reinforcement learning, performance optimization, or advanced system architecture design.

Benefits:

• Competitive compensation aligned with experience and market standards.
• Opportunity to work on cutting-edge AI, deep learning, and reinforcement learning systems at scale.
• Fully remote or flexible work arrangements depending on team structure and location.
• Exposure to large-scale distributed systems and high-performance computing environments.
• Strong emphasis on research-driven engineering and continuous innovation.
• Collaborative, highly technical environment working alongside experienced engineers and researchers.
• Opportunity to directly impact production systems powering global logistics and supply chain intelligence.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1