Remote opportunity at
WaabiTechnical Lead Manager, ML Dataset Platform
Waabi operates as a physical AI enterprise specializing in autonomous transportation technology for commercial trucks and robotaxis, led by AI specialist Raquel Urtasun. The company maintains…
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About This Role
Waabi operates as a physical AI enterprise specializing in autonomous transportation technology for commercial trucks and robotaxis, led by AI specialist Raquel Urtasun. The company maintains locations in San Francisco, Toronto, Dallas, and Pittsburgh. A full-time Technical Lead Manager for the ML Dataset Platform is currently sought by the organization to work remotely. This position involves leading a team while maintaining hands-on engineering contributions. The incoming professional will design storage…
Job Description
Waabi operates as a physical AI enterprise specializing in autonomous transportation technology for commercial trucks and robotaxis, led by AI specialist Raquel Urtasun. The company maintains locations in San Francisco, Toronto, Dallas, and Pittsburgh. A full-time Technical Lead Manager for the ML Dataset Platform is currently sought by the organization to work remotely. This position involves leading a team while maintaining hands-on engineering contributions. The incoming professional will design storage formats, tooling, and application programming interfaces that treat datasets as a primary asset across the company. Success in the role requires balancing standardization with flexibility to accommodate various machine learning pipelines without forcing a single approach onto every development group.
This opportunity suits an engineering leader experienced in large-scale machine learning data infrastructure who enjoys guiding teams, shaping technical strategies, and building consensus. Responsibilities include establishing dataset versioning systems, building incremental update mechanisms, improving training job throughput, automating data lineage tracking, and collaborating closely with model training platform teams. Candidates will guide the adoption of shared dataset tools by migrating existing workflows onto the unified platform.
Responsibilities
- Manage and expand the machine learning dataset platform team by hiring, mentoring, and setting the technical roadmap
- Design application programming interfaces, tools, and storage formats for datasets while balancing reuse against specific training workload needs
- Develop scale-appropriate dataset management tools supporting versioning and incremental updates without requiring full rebuilds
- Create interfaces allowing teams to specify training-time transformations spanning advance ETL and dynamic data loader execution
- Oversee common data loading utilities and monitor performance bottlenecks and training job throughput
- Optimize multi-cloud data access to ensure dataset availability with controlled cost and latency
- Implement automated data lineage tracking spanning from raw sources to trained models
- Collaborate with the machine learning training platform group and model development teams to drive migration onto the new infrastructure
Requirements
- Extensive background in machine learning dataset infrastructure including storage formats, versioning, ETL, and data loading for petabyte-scale sensor or multimodal data
- Proficiency in Python and familiarity with PyTorch training loops
- Software engineering fundamentals with practical exposure to distributed systems, cloud storage, and processing frameworks such as Spark, Ray, or Beam
- Demonstrated technical leadership in defining application programming interfaces and driving multi-team adoption of a platform or infrastructure initiative
- People management or technical leadership experience involving hiring, mentoring, roadmap execution, and stakeholder coordination
- Communication skills necessary to align researchers and engineers across multiple groups in a rapid environment
Qualifications
- Familiarity with machine learning data infrastructure within robotics or autonomous driving domains including multi-sensor logs, LiDAR, camera data, and HD maps
- Familiarity with columnar and tensor storage formats such as Parquet, Lance, WebDataset, or Zarr alongside dataset versioning utilities
- Exposure to multi-cloud or hybrid training environments and associated data movement challenges
- Background working with data lineage systems, metadata catalogs, or feature stores
Core Skills
Benefits
- Competitive compensation and equity awards
- Health and wellness benefits including medical, dental, and vision coverage for full-time employees
- Unlimited vacation policy
- Flexible working hours and work from home support
- Daily drinks, snacks, and catered meals when working from an office
- Regularly scheduled team building activities and social events held on-site, off-site, and virtually
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the remote policy for this role?
The position is designated as remote.
What is the salary range for the Technical Lead Manager position?
The yearly salary range in the United States is between $200,000 and $280,000 USD, supplemented by equity incentive awards and an annual performance bonus.
What type of employment is this?
This is a full-time employment opportunity.
What technical background is required for applicants?
Candidates must have deep experience with large-scale machine learning data infrastructure, strong Python and PyTorch skills, and a background in distributed systems, cloud storage, and data processing frameworks.
Sample Interview Questions
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