Staff Machine Learning Engineer

Job Description

We’re looking for a Staff Machine Learning Engineer to join Procore’s AI Studios team. In this role, you will play a pivotal role in driving AI advancements that revolutionize the construction industry. Procore is the leading construction management platform, empowering teams to seamlessly connect field and office operations. Trusted by thousands of construction professionals worldwide, Procore sets the standard for innovation and excellence in the industry.

As a Staff Machine Learning Engineer in the Construction Intelligence division, your contributions will enable smarter workflows, improve efficiency, and elevate decision-making processes for construction teams globally. This is an exciting opportunity to work on impactful projects, leveraging state-of-the-art AI technologies to tackle some of the industry’s biggest challenges.

We believe in extreme passion and relentless drive to do our best work every single day. Procorians are resilient, self-motivated, and selfless. If this resonates with you, please consider applying today!

This position reports to the Director of Machine Learning in the Construction Intelligence division and will be based in our Toronto, ON, Canada office. We’re looking for someone to join us immediately.

What you’ll do:

1. Interact with customers directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them.
2. Research, develop, and implement the state-of-the-art solutions in AI and ML to develop and deploy scalable solutions into production.
3. Collaborate and coordinate with people in a range of roles, including product managers, designers, engineers, and other key product stakeholders to define requirements, scope, and architecture for new features and enhancements.
4. Pushing forward what we’re doing with AI technology – not just executing but helping to discover and keep Procore on the leading edge.
5. Be an excellent communicator and share knowledge by clearly articulating results and ideas to customers, managers, and key decision makers.
6. Foster a healthy and inclusive team environment, provide technical guidance to other engineers, and act as a mentor.

What we’re looking for:

1. 5+ years of Python experience focused on scalable, maintainable code.
2. Experience in training and deploying models using PyTorch and TensorFlow (including YOLOv8-v11, Transformers, Mask R-CNN, DETR, and Swin Transformers).
3. Proficient in fine-tuning LLMs, VLMs, and NLP technologies for specialized applications.
4. Skilled in designing workflows for data collection, annotation, feature engineering, model training, and evaluation.
5. Proficient in distributed GPU training with CUDA and cuDNN for multi-GPU systems.
6. Proficient in containerization, microservices, and deployment using Docker, Kubernetes, and cloud platforms like AWS.
7. Strong knowledge of Ray for distributed execution, ArgoCD for GitOps workflows, and Kubernetes for managing ML applications.
8. Proficient in Git and building robust CI/CD pipelines to ensure efficient development and deployment.
9. Experience with monitoring tools like Datadog, New Relic, and Sumo Logic for ensuring system reliability and performance.
10. Solid understanding of Agile practices with a proven track record of delivering iterative, high-quality results.

About Us

Procore Technologies is building the software that builds the world. We provide cloud-based construction management software that helps clients more efficiently build skyscrapers, hospitals, retail centers, airports, housing complexes, and more. At Procore, we have worked hard to create and maintain a culture where you can own your work and are encouraged and given resources to try new ideas. Check us out on Glassdoor to see what others are saying about working at Procore.

We are an equal-opportunity employer and welcome builders of all backgrounds. We thrive in a diverse, dynamic, and inclusive environment. We do not tolerate discrimination against candidates or employees on the basis of gender, sex, national origin, civil status, family status, sexual orientation, religion, age, disability, race, traveler community, status as a protected veteran or any other classification protected by law.