Technical Lead Manager, ML Dataset Platform

Location: Hybrid in San Francisco, CA; other locations include Toronto, ON and Pittsburgh, PA; remote work available in the US and Canada.

Salary: $200,000–$280,000 USD yearly, plus equity incentive awards and an annual performance bonus.

Company

hirify.global is a technology startup developing Physical AI for commercial autonomous trucks and robotaxis.

What you will do

• Lead and grow the ML Dataset Platform team as technical lead and people manager, including technical direction, roadmap ownership, hiring, and mentoring.
• Define APIs, tooling, and storage formats for reusable ML datasets, including versioning and efficient incremental updates.
• Design training-time transformation APIs spanning reproducible ETL and dynamic data-loader transformations.
• Own shared dataloading tools, observability into bottlenecks, and training throughput across workloads.
• Streamline multi-cloud dataset access with predictable cost and latency, and make data lineage automatic from raw data to trained models.
• Partner with ML Training Platform and ML development teams to migrate training data, drive adoption, and shape the platform roadmap.

Requirements

• Experience designing and building large-scale ML training data infrastructure, including storage formats, dataset versioning, ETL, and dataloading.
• Understanding of performance characteristics for petabyte-scale sensor or multimodal data.
• Very strong Python skills and comfort working with PyTorch training loops.
• Strong software-engineering fundamentals and experience with distributed systems, cloud storage, and data-processing frameworks such as Spark, Ray, or Beam.
• Experience leading a platform or infrastructure effort used by multiple teams, defining APIs, and driving organizational adoption.
• Experience managing or tech-leading engineers, including hiring and mentoring, while balancing hands-on contribution, roadmap ownership, and stakeholder management.
• Clear communication with researchers and engineers, consensus-building across teams with different needs, and delivery in a fast-paced environment.

Nice to have

• ML data infrastructure experience in autonomous driving or robotics, including multi-sensor logs, LiDAR, cameras, or HD maps.
• Experience with columnar and tensor storage formats such as Parquet, Lance, WebDataset, or Zarr, and dataset versioning tools.
• Experience with multi-cloud or hybrid training environments and related data-movement challenges.
• Experience with data lineage, metadata catalogs, or feature-store systems.

Culture & Benefits

• Full-time employment with medical, dental, and vision coverage.
• Unlimited vacation, flexible hours, and work-from-home support.
• Competitive compensation, equity awards, and an annual performance bonus.
• Daily drinks, snacks, and catered meals when working in the office.
• Regular team-building and social events held on-site, off-site, and virtually.
• Inclusive, supportive, and accessible workplace with accommodations available for qualified applicants.