Senior Software Engineer

Source One is a staffing services company and we’re currently looking for the following individual to work as a consultant to our direct client, a ride-sharing autonomous vehicle company in Foster City, CA.

** We are unable to work with third-party companies for this role.

Title: Senior Software Engineer - Perception Auto-Labeling Pipeline (Contract)

Schedule: Hybrid - 3 days onsite per week

Pay Rate: $87.40/hour

About the Role: Our client is seeking a Software Engineer to join the Perception Attribute Flywheel team and build the auto-labeling infrastructure that accelerates machine learning development for autonomous vehicles. In this role, you'll develop and operate large-scale data pipelines that leverage foundation models such as Gemini, CLIP, and SigLIP to generate pre-labeled perception data. Your work will directly improve annotation efficiency, data quality, and the speed at which perception models are developed and deployed across the autonomous vehicle stack. You'll collaborate closely with Machine Learning, Perception, and Data Infrastructure teams to build reliable, observable, and scalable systems that support high-volume annotation workflows.

Responsibilities

• Design, build, and maintain auto-labeling pipelines that ingest annotation tasks and generate pre-labels using foundation model APIs.

• Integrate large-scale foundation model services (Gemini and similar models) into production data workflows.

• Process and validate structured model outputs before returning them to annotation and labeling systems.

• Develop monitoring and observability solutions to track pipeline health and reliability, request latency, model utilization and cost, attribute coverage, and error conditions and failure modes.

• Support ML experimentation by preparing datasets, running evaluation workflows, and collecting outputs for analysis.

• Collaborate with Perception, Machine Learning, and Infrastructure teams to integrate pipeline components into existing systems.

• Troubleshoot production issues, optimize performance, and improve operational reliability.

• Create technical documentation, design documents, operational runbooks, and support procedures to ensure long-term maintainability.

Required Qualifications

• 3+ years of experience building backend systems or large-scale data pipelines

• Strong programming experience in Python

• Working knowledge of C++

• Experience processing and managing large datasets using PySpark or equivalent distributed data frameworks

• Understanding of machine learning fundamentals, including Model inference, Embeddings, Structured outputs, or Evaluation metrics (precision, recall, calibration)

• Experience integrating foundation models or LLM services (Gemini, OpenAI, Anthropic, etc.) into production systems

• Experience designing scalable, reliable, and observable backend services

• Strong written communication skills, including experience creating design documentation and operational runbooks

Preferred Qualifications

• Experience with Databricks

• Ownership of production ML systems from data ingestion through inference, monitoring, and operations

• Experience supporting annotation platforms or human-in-the-loop machine learning workflows

• Background working with autonomous vehicle, robotics, or perception data pipelines

• AWS experience, including services such as S3, ECS/EKS or Lambda

• Experience working in shared codebases with machine learning engineers, including schema management and coordinated deployments