Software Engineer

Software Engineer

A position is available for a Software Engineer to build and operate an autolabeling pipeline. This system is designed to accelerate human annotation throughput on vehicle attribute classification tasks. The role involves owning the pipeline engineering, including ingesting tasks, calling foundation-model APIs, writing predictions into the labeling workflow, and ensuring reliable operation. This is an opportunity to build reliable, observable, and well-tested data pipelines that will accelerate an autonomous vehicle program.

Key Responsibilities

• Build the autolabeling pipeline, including ingesting tasks, dispatching them to foundation-model APIs, parsing outputs, and writing pre-labels back to the workflow.
• Develop the observability layer, creating dashboards for latency, cost, coverage, and error modes.

Required Qualifications

• 3+ years of backend or data pipeline engineering experience.
• Proficiency in Python and comfort with C++.
• Experience with large datasets using PySpark or an equivalent technology.
• A fundamental understanding of machine learning concepts, including model inference, embeddings, structured output, and common evaluation metrics.
• Experience integrating foundation models at a production scale.
• Excellent written communication skills for creating design documents and runbooks.

Preferred Qualifications

• Experience with Databricks.
• History of end-to-end ML pipeline stewardship in a production environment.
• Familiarity with annotation tooling or human-in-the-loop ML workflows.
• Experience with autonomous-systems data pipelines.
• Knowledge of AWS services, particularly S3, ECS/EKS, and Lambda.
• Experience working in a codebase shared with machine learning engineers.