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Torc Robotics, now part of the Daimler family, is developing autonomous trucking software to transform freight transportation. As a Software Engineer II on the Fleet Enablement & Insights team, you will design and build the tooling and data systems that enable fleet operations to optimize autonomy data collection. Your work directly impacts the infrastructure that determines what data is collected, validates data quality and safety for the autonomous truck platform, and measures machine learning needs against collection priorities.
Key responsibilities include designing and developing Python-based tools and services for fleet data-collection planning, metrics, and data-readiness pipelines. You'll build internal tooling to automate route prioritization, data-collection setup, asset tracking, and data ingestion/validation workflows. You'll develop fleet metrics and surface them in live dashboards for real-time quality monitoring during missions. You'll contribute to map tooling that uses simulation and topology evaluation to validate mapping updates before release.
You'll manage relational and spatial databases (PostgreSQL, SQLite) ensuring data integrity and performance across fleet, collection, and mapping datasets. Leverage AWS services (S3, Lambda, ECS, RDS) and Databricks to build scalable data pipelines and analytics infrastructure. Collaborate with Fleet Operations, Mapping, Perception, Localization, and Data Annotation teams to align data-collection capabilities with downstream requirements. Participate in agile ceremonies and cross-team syncs. Contribute to engineering excellence through code reviews, documentation, and knowledge sharing. Identify and address technical debt, performance bottlenecks, and reliability gaps.
Required qualifications: Proficiency in Python for production-quality tools and services; strong SQL expertise for querying and analyzing relational/analytical data; working knowledge of C++ and TypeScript; strong database expertise with PostgreSQL and SQLite; experience with Databricks for large-scale data processing; experience building metrics and analytics pipelines; proficiency with Git/GitHub; familiarity with JIRA; solid software engineering fundamentals; strong communication skills; Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent experience).
Bonus qualifications include experience with simulation systems, data visualization tools (Databricks, Plotly, Grafana), PostGIS for geospatial queries, HD maps and map formats (OpenDRIVE, NDS, Lanelet2), routing/optimization algorithms, autonomous vehicle or machine learning background, and open-source contributions.
