Note: The job is a remote job and is open to candidates in USA. Torc Robotics is a leader in autonomous driving technology, focused on developing software for automated trucks. They are seeking a Senior Software Engineer to integrate and deploy automated event-tagging systems, build data engineering pipelines, and maintain CI/CD processes to support high-volume data processing.
Responsibilities
- Integrate and deploy automated event-tagger into production pipelines, running and monitoring tagging tasks at scale across petabytes of vehicle log data
- Build and maintain the data engineering pipelines that organize, structure, and catalog tagged scenario data into the observations database
- Own CI/CD for the Auto Tagger pipeline using GitHub Actions, keeping deployments reliable, tested, and repeatable
- Write production grade code in Python across the pipeline, from data ingestion and transformation through model integration and deployment
- Build and operate on Databricks for large scale data processing, interactive querying, and pipeline orchestration
- Design, deploy, and scale AWS infrastructure (as code) to support high-volume, distributed processing of vehicle log pipelines — working with structured/tagged outputs and metadata
- Instrument pipelines with logging, metrics, and alerting; own on-call response for tagging job failures and data quality regressions
- Partner with ML engineers on the team to take tagging and classification models from development into a scalable, monitored production pipeline
- Ensure data quality and metadata integrity as tagged events move from raw logs into the observations database used by perception, simulation, and systems teams
- Troubleshoot and improve pipeline performance, reliability, and cost as data volume and model complexity grow
Skills
- BS or MS in Computer Science, Engineering, or a related field, with 5+ years of software engineering experience, including production data pipeline or ML infrastructure work
- Strong Python skills, with experience building and maintaining production data or ML pipelines
- Hands-on CI/CD experience, GitHub Actions required
- Required experience with Databricks for large scale data processing and orchestration
- Required experience with AWS, including infrastructure-as-code (Terraform or CloudFormation) for provisioning distributed processing infrastructure
- Experience processing large scale time series or unstructured datasets
- Experience with observability tooling (e.g., Datadog, Grafana, CloudWatch) for production pipeline monitoring and alerting
- Experience integrating and deploying ML models into production systems — serving, monitoring, and rollback, not just training
- Strong communication skills to work across ML, perception, and simulation teams
- Familiarity with auto-labeling pipelines, VLMs, or zero-shot classification for scenario extraction
- Experience with distributed compute frameworks such as Ray, Spark, or Daft
- Familiarity with robotics data formats (ROS bags, MCAP) and columnar storage formats (Parquet, Arrow)
- Experience with model serving frameworks such as vLLM or SGLang
- Familiarity with scenario description standards like Pegasus layers
Benefits
- A competitive compensation package that includes a bonus component and stock options
- 100% paid medical, dental, and vision premiums for full-time employees
- 401K plan with a 6% employer match
- Flexibility in schedule and generous paid vacation (available immediately after start date)
- Company-wide holiday office closures
- AD+D and Life Insurance
Company Overview
Company H1B Sponsorship