Senior Software Engineer - AutoTagging

This is a fully remote position, open to applicants in Michigan.

📋 Description

• Implement and deploy the automated event-tagger within production pipelines, overseeing and monitoring tagging operations at scale across petabytes of vehicle log data.

• Develop and sustain data engineering pipelines that organize, structure, and catalog tagged scenario data into the observations database.

• Manage CI/CD for the Auto Tagger pipeline utilizing GitHub Actions.

• Produce production-quality Python code for data ingestion, transformation, model integration, and deployment.

• Create and operate on Databricks for extensive data processing, interactive querying, and pipeline orchestration.

• Design, implement, and scale AWS infrastructure as code for high-volume, distributed vehicle-log processing.

• Integrate pipelines with logging, metrics, and alerting; take responsibility for on-call responses to tagging failures and data-quality regressions.

• Collaborate with ML engineers to transition tagging and classification models into scalable, monitored production pipelines.

• Ensure the quality of data and the integrity of metadata within the observations database.

• Diagnose and enhance pipeline performance, reliability, and cost-effectiveness as data volume and model complexity increase.

⛳️ Requirements

• A BS or MS in Computer Science, Engineering, or a related discipline, coupled with 5+ years of software engineering experience, including work on production data pipelines or ML infrastructure.

• Proficient in Python with experience in building and maintaining production data or ML pipelines.

• Practical CI/CD experience; GitHub Actions are mandatory.

• Essential experience with Databricks for large-scale data processing and orchestration.

• Required familiarity with AWS, including infrastructure as code utilizing Terraform or CloudFormation.

• Experience in processing large-scale time-series or unstructured datasets.

• Familiarity with observability tools such as Datadog, Grafana, or CloudWatch.

• Experience in integrating and deploying ML models into production systems, including serving, monitoring, and rollback capabilities.

• Strong communication skills to collaborate effectively across ML, perception, and simulation teams.

• Bonus: Knowledge of auto-labeling pipelines, VLMs, zero-shot classification, Ray, Spark, Daft, ROS bags, MCAP, Parquet, Arrow, vLLM, SGLang, or Pegasus layers.

🏝️ Benefits

• A competitive compensation package that includes a bonus component and stock options.

• Full coverage of medical, dental, and vision premiums for full-time employees.

• 401K plan featuring a 6% employer match.

• Flexible scheduling and generous paid vacation available immediately upon start date.

• Company-wide holiday office closures.

• AD+D and Life Insurance.

• Potential sign-on bonuses, relocation assistance, and other compensation forms based on the position offered.