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About the Role

Design and build data systems powering frontier-scale machine learning research and applied AI products, focusing on spatial intelligence and multimodal data. Ensure researchers and engineers can reliably discover, curate, transform, and operate on large-scale datasets from experimentation to production. Provide technical leadership in data architecture, quality, and operational excellence to shape how Procore builds, evaluates, and deploys frontier models.

Responsibilities

Act as the technical lead for data engineering efforts supporting frontier model research and applied ML systems.
Design, build, and maintain scalable batch and streaming pipelines for multimodal data (e.g., documents, images, spatial metadata).
Partner closely with researchers and architects to translate experimental workflows into reliable, repeatable data systems.
Lead the development of dataset curation, versioning, and lineage workflows that support rapid experimentation and reproducibility.
Establish and uphold standards for data quality, validation, observability, and cost efficiency across AI data pipelines.
Contribute to data architecture decisions spanning research environments and production systems.
Identify gaps or inefficiencies in existing data workflows and run proofs-of-concept to evaluate improvements.
Mentor other engineers through code reviews, design discussions, and hands-on collaboration.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
8+ years of experience designing and operating complex data systems in production or research-adjacent environments.
Strong proficiency in SQL and Python; experience with data-intensive or distributed systems.
Proven experience building scalable data pipelines that support machine learning training, evaluation, or inference workflows.
Solid understanding of data modeling, dataset lifecycle management, and data quality best practices.
Comfort operating in highly ambiguous problem spaces and collaborating closely with researchers and architects.
Demonstrated ability to lead through direct technical contribution, mentorship, and setting engineering standards.
Strong communication skills, with the ability to explain technical tradeoffs to both research and engineering audiences.

Skills

SQL
Python
Data modeling
Dataset lifecycle management
Data quality best practices
Large-scale dataset curation
Annotation workflows
Experiment tracking
Reproducibility tooling
Databricks
Spark
Lakehouse architectures
Cloud data warehouses
Kafka
Pub/Sub
Event-driven data architectures
Airflow
Dagster
Data quality tools
Data lineage tools
AWS
GCP
Containerized data workloads
CI/CD
Infrastructure-as-code
Optimizing data pipelines for GPU-backed training
Optimizing data pipelines for large-scale inference workloads

Location

San Francisco

Work Type

Hybrid

Experience Level

8+ years

Education Level

Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Salary/Compensations

227,332.00 - 312,581.50 USD Annual
This role may also be eligible for Equity Compensation and/or Bonus Incentive Compensation.

About the Company

Procore is committed to offering competitive, fair, and commensurate compensation.

Equal Opportunity

For Los Angeles County (unincorporated) Candidates: Procore will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable federal, state, and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
A criminal history may have a direct, adverse, and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: 1. appropriately managing, accessing, and handling confidential information including proprietary and trade secret information, as well as accessing Procore's information technology systems and platforms; 2. interacting with and occasionally having unsupervised contact with internal/external customers, stakeholders, and/or colleagues; and 3. exercising sound judgment.