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.