Software Engineer, II - Autonomy Data

Remote - USfull timeRemote

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mid

$139k–$167k

H1B: no

Torc Robotics Software Engineer II - Autonomy Data at Torc Robotics designs and operates data infrastructure for autonomy programs. Responsibilities include building data lakes, ingestion pipelines, dataset curation tools, and visualization tooling to support perception, planning, and simulation engineers.

Responsibilities

Data Lake and Ingestion Pipeline
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 ingest high-bandwidth sensor logs from vehicles into cloud storage with high reliability and tolerant of ad-hoc and intermittent connectivity mechanisms.
Implement data validation and integrity checks that can detect corrupted information, missing sensors, and inconsistent calibration prior to the data being processed by downstream systems.
Implement retention, tiering and lifecycle policies for data to balance storage costs with development value.
Dataset Curation and Labeling Infrastructure
Build tooling to query raw logs to produce curated training and evaluation datasets.
Build automation to run cost-effective pseudo-labeling workflows at the scale of data ingest.
Implement data quality and model performance metrics that are used to direct labeling effort toward the highest-value examples.
Autonomy Data Visualization
Deploy and maintain data visualization tooling to support log review, annotation QA, and autonomy debugging workflows.
Build integrations between the visualization tooling and the data lake so engineers can navigate from a dataset entry or model failure directly to the origin log data

Qualification

Bachelor’s degree in Computer ScienceStrong proficiency in Python and SQLExperience with autonomous vehicles

Required

Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, Electrical Engineering or a related field with 4+ years of data engineering experience or a Master’s with 2+ years.
Strong proficiency in Python and SQL, with demonstrated ability to build production-quality data pipelines
Experience with cloud data infrastructure (AWS preferred: S3, Glue Athena, redshift, or equivalent) and infrastructure-as-code tools (Terraform, Cloud Formation).
Solid understanding of data partitioning strategies and columnar storage formats (Parquet, Orc, etc.)
Experience building and operating data pipelines that process time-series and binary data.
Proven ability to evaluate and integrate open-source tooling when appropriate versus building from scratch.
Good instincts for delivering data quality through first-class implementations of monitoring, validation and lineage tracking.

Preferred

Experience with autonomous vehicles, robotics, or other sensor-driven autonomous systems.
Deep experience with Foxglove or Rerun beyond basic playback, e.g. building custom extensions or integrating them into a structured log review or annotation QA workflow.
Familiarity with the MCAP CLI and/or python library and experience converting MCAP data to columnar data formats for further querying and processing.
Experience with data curation for ML training, e.g. diversity sampling, pseudo-labeling, and dataset versioning.
U.S. Citizenship Requirement:
This position requires access to information and systems that are restricted under U.S. law. Accordingly, only U.S. citizens are eligible for this role. This requirement is based on applicable government regulations and is not related to immigration status discrimination.