AI Platform & Machine Learning Engineer

Help build the AI platform powering the future of construction

At XYZ Reality weve created the worlds first engineering-grade Augmented Reality solution for construction. Our technology is already being used on major construction projects around the world to help teams build more accurately efficiently and with fewer mistakes.

Now were taking that technology even further.

Were developing the next generation of wearable AI systems combining computer vision localisation BIM understanding semantic reasoning and augmented reality to create a Construction Intelligence platform capable of understanding what has been built where it has been built and whether it has been installed correctly.

As a Series B business entering our next phase of growth were investing further in our R&D capability and building out a new technology hub in Calgary Canada.

Were looking for an AI Platform & Machine Learning Engineer to join us and help build the infrastructure that will power the next generation of our AI products.

The Role

This is an exciting opportunity for a Machine Learning Engineer who wants to work at the point where AI research meets real-world production engineering.

Youll work on the systems that enable our AI models to move from research and experimentation into scalable production-ready technology building the infrastructure for dataset management model training and retraining experiment tracking continual learning deployment and monitoring.

A key part of the role will be understanding the complete AI lifecycle: from acquiring and labelling data through to training models evaluating their performance and ultimately deploying them into production.

Working closely with our Computer Vision Navigation Embedded Software and Cloud Engineering teams youll help ensure our AI models can be trained evaluated deployed and continually improved throughout the product lifecycle.

This is an exciting time to join! Youll have the opportunity to work alongside deep technical expertise while having a genuine influence on how our AI platform evolves as we scale.

This isnt AI for AIs sake. The technology you build will ultimately support wearable systems being used in real-world construction environments solving complex problems and changing how some of the worlds largest projects are delivered.

What Youll Be Doing

• Design and build scalable infrastructure for training and deploying machine learning models.

• Develop distributed training pipelines and reproducible training environments.

• Build experiment tracking model versioning and model registry capabilities.

• Develop automated benchmarking and model validation pipelines.

• Build large-scale dataset ingestion management and validation workflows.

• Develop annotation and labelling workflows to support high-quality AI training data.

• Explore synthetic data generation where appropriate.

• Design and improve CI/CD pipelines for machine learning.

• Monitor deployed model performance and support automated retraining.

• Develop continual learning pipelines and explore techniques including PEFT and LoRA.

• Support federated learning and improve model lifecycle management.

• Deploy AI models across cloud services and embedded NVIDIA platforms.

• Optimise inference infrastructure and build scalable APIs supporting AI services.

• Work closely with AI Computer Vision Navigation Embedded and Cloud teams to turn research into production-quality systems.

• Contribute to technical architecture decisions engineering standards and automation across the wider R&D team.

What Were Looking For

• Minimum of 35 years experience in Machine Learning Engineering or a closely related role.

• Degree in Computer Science Artificial Intelligence Software Engineering or a related discipline; Masters level or above is preferred.

• Strong Python development skills and hands-on experience with PyTorch.

• Practical experience training and retraining machine learning models were looking for someone who understands what happens beyond simply consuming existing AI models.

• Experience building and maintaining production ML pipelines.

• Strong understanding of the end-to-end ML lifecycle from acquiring and preparing data through to training evaluation deployment and monitoring.

• Experience with computer vision and modern AI/model architectures.

• Experience with Docker Kubernetes and CI/CD.

• Experience deploying machine learning models within cloud environments.

• Strong software engineering fundamentals and an understanding of how to build reliable maintainable production systems.

• Comfortable working in a fast-moving area where technologies and approaches continue to evolve rapidly.

Experience with technologies such as MLflow Weights & Biases Ray Kubeflow Airflow LoRA PEFT NVIDIA Jetson CUDA TensorRT or ONNX would be highly valuable as would experience with AWS Azure or GCP and large-scale dataset management.

You dont need to have worked with every technology on the list. Were particularly interested in people who can demonstrate strong ML engineering fundamentals genuine hands-on experience and the ability to learn and adapt as the technology evolves.

Above all were looking for someone who is curious collaborative and excited by solving difficult technical problems someone who wants to help turn cutting-edge AI research into technology that works in the real world.

What You Could Be Working On

From the outset youll have the opportunity to contribute to high-priority projects including:

• AI training infrastructure

• Continual learning platform

• Model registry and experiment tracking

• Automated benchmarking frameworks

• Cloud-to-edge deployment pipelines

• Embedded AI deployment

• Wearable Construction Intelligence technology

• Work at the intersection of AI Computer Vision AR and real-world engineering

• Help build production AI systems tackling genuinely complex technical problems

• See your work applied to some of the worlds most ambitious construction projects

• Join a Series B business at an exciting stage of international growth

• Work alongside specialists across AI Computer Vision Navigation and Embedded Engineering

• Have meaningful input into the architecture and evolution of our next-generation AI platform

• Build technology with real-world global impact

If youre excited by the challenge of taking machine learning from experimentation through to scalable production and want to help build the AI infrastructure behind the future of construction wed love to hear from you.

Required Experience:

IC