Title:
AV Safety Data Engineer
Job Type: Contract
Contract Length: 6+ months
Target Start Date: ASAP
Work Location/Structure: Onsite - Foster City, CA
About the Opportunity:
Our client, a leader in the Autonomous Vehicle industry, is looking for a skilled AV Safety Data Engineer to join their team for a 6+ month engagement. This project involves developing and maintaining robust data infrastructure to surface safety-relevant interactions, assess AV events, and inform autonomy development through data-driven insights, ensuring autonomous vehicles operate safely and meet all federal and state compliance requirements. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly.
Key Responsibilities & Deliverables:
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
Job Type: Contract
Contract Length: 6+ months
Target Start Date: ASAP
Work Location/Structure: Onsite - Foster City, CA
About the Opportunity:
Our client, a leader in the Autonomous Vehicle industry, is looking for a skilled AV Safety Data Engineer to join their team for a 6+ month engagement. This project involves developing and maintaining robust data infrastructure to surface safety-relevant interactions, assess AV events, and inform autonomy development through data-driven insights, ensuring autonomous vehicles operate safely and meet all federal and state compliance requirements. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly.
Key Responsibilities & Deliverables:
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
- Developing and maintaining miners that identify events of interest from fleet and simulation data.
- Improving the accuracy and efficiency of existing miners through advanced statistical and ML techniques.
- Building scalable data pipelines and dashboards to monitor miner performance, signal quality, and key safety metrics.
- Conducting exploratory data analyses to uncover trends, failure modes, and opportunities to improve vehicle behavior.
- Triaging and assessing AV events for potential safety/legal/regulatory concerns or system gaps.
- Developing and maintaining clear triage guidelines and criteria for both onshore and offshore triage teams.
- Supporting regulatory reporting processes by providing data and analysis as needed.
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
- 6-8 years of experience working with safety-critical systems in AV, Automotive, Transportation Engineering, or a closely related industry (4+ years if they have an AV background).
- Strong programming skills in Python and SQL.
- Experience with large datasets and distributed data processing frameworks (e.g., Spark, Databricks).
- Strong data engineering skills, including data wrangling and expertise in building maintainable, scalable, and efficient data pipelines.
- Familiarity with statistics and probability, and experience with sampling and estimation methodologies.
- Proven ability to design metrics, run analyses, and translate findings into actionable recommendations.
- Strong understanding of behavioral safety concepts and the ability to interpret vehicle behavior in real-world contexts, along with knowledge of AV requirements, road user behavior, and traffic regulations.
- Experience working with cross-functional teams and clearly communicating technical content to both engineering and non-technical audiences.
- Strong organizational skills with attention to detail, especially in process development and documentation related to data pipelines and safety analysis.
- Master’s Degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative or Engineering field.
