Principal Applied Research Scientist (Datagrid)

About the role

We’re looking for a Principal Applied Research Scientist to join Procore’s AI & Frontier Models organization. In this role, you’ll lead applied research and system development at the intersection of machine learning, spatial reasoning, and construction data to solve some of the industry’s most complex and ambiguous problems.

Responsibilities

• Lead the technical vision, design, and execution of applied research initiatives focused on spatial intelligence across 2D drawings, BIM, and site data.
• Design, train, and evaluate machine learning models for constructability analysis, clash detection, and design risk identification.
• Build high-quality, proprietary annotated datasets and define data strategies that create long-term competitive advantage.
• Translate ambiguous research problems into concrete system designs, proofs of concept, and production-ready ML pipelines.
• Partner closely with engineering and product teams to integrate research outputs into scalable, reliable systems.
• Act as a technical SME for spatial intelligence, mentoring senior engineers and researchers across the organization.
• Author and review technical documentation, white papers, and design proposals that shape Procore’s AI strategy.
• Proactively identify gaps in technical strategy and architecture, and independently drive solutions that improve system quality, robustness, and impact.

Requirements

• PhD or Master’s degree in Computer Science, Machine Learning, Robotics, Computer Vision, or a related field, or equivalent depth of practical experience.
• 12+ years of experience (or equivalent depth) building and leading complex machine learning or software systems in production and/or applied research environments.
• Demonstrated ability to set technical direction and independently lead high-impact initiatives across multiple teams or a significant business concern.
• Deep expertise in applied machine learning, with a track record of translating research ideas into scalable, reliable systems that deliver measurable outcomes.
• Strong foundation in computer science fundamentals, including algorithms, data structures, distributed systems, and system architecture.
• Proven ability to operate effectively in high-ambiguity problem spaces, using data, experimentation, and proof-of-concept work to create clarity and alignment.
• Experience mentoring senior engineers and researchers, and serving as a technical authority and escalation point across an organization.
• Excellent communication skills, with the ability to represent technical strategy, tradeoffs, and outcomes to senior leadership and cross-functional stakeholders.

Qualifications

• Nice to have experience with technologies such as: ML & Model Development: PyTorch, TensorFlow, large-scale pre-training or fine-tuning workflows, multimodal or foundation models
• Spatial Intelligence & Perception: Computer vision, document and diagram understanding, geometric or graph-based reasoning, 2D/3D representations
• Data & Research Infrastructure: Large-scale dataset creation and curation, annotation pipelines, distributed training, experiment management
• Systems & Architecture: Designing and evolving ML-powered platforms and services, cross-domain integrations, reliability and performance at scale
• Cloud & Compute: GPU/accelerator-based training and inference, containerized systems, Kubernetes, cloud platforms (AWS, GCP, or equivalent)
• Evaluation & Operations: Defining evaluation frameworks, model validation strategies, monitoring, and cost-aware optimization in production

What We’re Looking For

This role requires a PhD or Master’s degree in Computer Science, Machine Learning, Robotics, Computer Vision, or a related field, or equivalent depth of practical experience. It also requires 12+ years of experience (or equivalent depth) building and leading complex machine learning or software systems in production and/or applied research environments.

Base Pay Range

253,552.00 - 348,634.00 USD Annual