T

Torc Robotics

Autonomous truck software for Level 4

Software Engineer 2 - Autonomy Data

Data EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Electrical Engineering, or a related field plus 4 or more years of data engineering experience, or a master's degree plus 2 or more years of data engineering experience.
  • Strong proficiency in Python and SQL, with demonstrated ability to build production-quality data pipelines.
  • Experience with cloud data infrastructure, preferably AWS services such as S3, Glue, Athena, and Redshift, or equivalent, and infrastructure-as-code tools such as Terraform or CloudFormation.
  • Solid understanding of data partitioning strategies and columnar storage formats such as Parquet and ORC.
  • Experience building and operating data pipelines that process time-series and binary data.
  • Ability to evaluate and integrate open-source tooling when appropriate versus building from scratch.
  • Ability to deliver data quality through monitoring, validation, and lineage tracking.
  • Only U.S. citizens are eligible for this role because it requires access to information and systems restricted under U.S. law.

Responsibilities

  • Contribute to the design and organization of the program’s data lake, including schema definitions, partitioning strategy, and metadata indexing.
  • Build and maintain end-to-end pipelines that reliably ingest high-bandwidth sensor logs from vehicles into cloud storage, accommodating ad hoc and intermittent connectivity.
  • Implement data validation and integrity checks to detect corrupted information, missing sensors, and inconsistent calibration before downstream processing.
  • Implement retention, tiering, and lifecycle policies to balance storage costs with development value.
  • Build tooling to query raw logs and produce curated training and evaluation datasets.
  • Build automation for cost-effective pseudo-labeling workflows at the scale of data ingest.
  • Implement data quality and model performance metrics to direct labeling effort toward high-value examples.
  • Deploy and maintain data visualization tooling for log review, annotation quality assurance, and autonomy debugging workflows.
  • Build integrations between visualization tooling and the data lake so engineers can navigate from a dataset entry or model failure directly to the origin log data.
  • Work with autonomy engineers to define and surface custom visualization panels and implement metrics for analyzing unstructured operating environments.
  • Build dashboards that provide autonomy engineers visibility into data coverage by terrain type, operating environment, and geographic region.
  • Establish and document data contracts between data services and model-training consumers.
  • Partner with perception, planning, and embedded engineers across the data lifecycle, from shaping logging schemas and collection triggers to defining dataset interfaces for model training and evaluation.
  • Follow and help evolve data engineering standards, best practices, and tooling choices.
  • Contribute to the data roadmap and surface findings to senior technical leadership.

Desired Qualifications

  • Experience with autonomous vehicles, robotics, or other sensor-driven autonomous systems.
  • Experience with Foxglove or Rerun beyond basic playback, such as building custom extensions or integrating them into structured log-review or annotation quality assurance workflows.
  • Familiarity with the MCAP command-line interface or Python library, and experience converting MCAP data to columnar data formats for querying and processing.
  • Experience with data curation for machine learning training, such as diversity sampling, pseudo-labeling, and dataset versioning.

About the Company

Torc Robotics

Autonomous truck software for Level 4

Torc Robotics builds software for autonomous trucks, aiming to enable Level 4 self-driving capabilities for freight transport. They develop driving systems that let heavy trucks operate autonomously under certain conditions, and they work with truck manufacturers and fleet operators to bring these solutions to market. The company integrates sensors from partners (such as Luminar Technologies) and provides ongoing updates and support to ensure reliability and performance. Unlike more general AV players, Torc focuses on commercial trucking and leverages strategic partnerships (for example with Daimler Trucks) to integrate its software into production vehicles and fleets. Its goal is to improve road safety and freight efficiency by deploying scalable, commercial autonomous trucking solutions.

Company size
501-1,000
Company stage
M&A
Total funding
Not listed
Headquarters
Blacksburg, VA
Founded
2005

Recently Posted Jobs

Explore more opportunities at Torc Robotics

See more jobs