AI Platform & Machine Learning Engineer
XYZ Reality17 days ago
Calgary, CanadaMid Level / Senior
Responsibilities
- Design and build scalable infrastructure for training and deploying machine learning models.
- Develop distributed training pipelines, reproducible training environments, experiment tracking, model versioning, and model registry capabilities.
- Build automated benchmarking, model validation, dataset ingestion, management, and validation workflows.
- Develop annotation and labelling workflows and explore synthetic data generation for AI training data.
- Design and improve machine learning CI/CD pipelines, monitor deployed model performance, and support automated retraining.
- Develop continual learning pipelines, including techniques such as PEFT and LoRA, and support federated learning.
- Deploy AI models across cloud services and embedded NVIDIA platforms, optimize inference infrastructure, and build scalable AI service APIs.
- Collaborate with AI, Computer Vision, Navigation, Embedded, and Cloud teams to turn research into production-quality systems.
- Contribute to technical architecture, engineering standards, automation, and the evolution of the AI platform.
Requirements
- Minimum 3–5 years of experience in Machine Learning Engineering or a closely related role.
- Degree in Computer Science, Artificial Intelligence, Software Engineering, or a related discipline; Master’s level or above is preferred.
- Strong Python development skills and hands-on experience with PyTorch.
- Practical experience training and retraining machine learning models, including understanding the underlying model-development process rather than only consuming existing models.
- Experience building and maintaining production ML pipelines and understanding the end-to-end ML lifecycle.
- Experience with computer vision and modern AI/model architectures.
- Experience with Docker, Kubernetes, and CI/CD, plus deploying machine learning models in cloud environments.
- Strong software engineering fundamentals and the ability to build reliable, maintainable production systems.
- Experience with MLflow, Weights & Biases, Ray, Kubeflow, Airflow, LoRA, PEFT, NVIDIA Jetson, CUDA, TensorRT, ONNX, AWS, Azure, GCP, or large-scale dataset management is highly valuable.
- Curiosity, collaboration, adaptability, and enthusiasm for solving difficult technical problems are valued.
Benefits
- Work at the intersection of AI, Computer Vision, augmented reality, and real-world engineering.
- Help build production AI systems used in complex construction environments.
- See technology applied to major construction projects around the world.
- Join a Series B business undergoing international growth.
- Work alongside specialists across AI, Computer Vision, Navigation, and Embedded Engineering.
- Have meaningful input into the architecture and evolution of the AI platform.
- The role is based in the company’s new technology hub in Calgary, Canada.
Tech Stack
Categories