Validation Analytics Tools Developer

The AV Validation teams are looking for an experienced Python developer with a strong background in data analytics and AI-enabled tools to develop metrics, methodologies, and applications for evaluating autonomous-vehicle sensing performance.

The AV Validation organization is responsible for evaluating the safety, quality, and performance of autonomous-vehicle systems. Our team combines large-scale validation data, analytics, and modern AI capabilities to develop tools and methodologies that help engineers understand sensing behavior, identify performance gaps, and measure progress across AV software versions.

What will your job look like:

• Design, develop, and maintain Python-based analytics applications and internal tools for AV validation
• Develop metrics, reports, and methodologies for measuring Sensing State performance across software versions.
• Build tools for event investigation, data exploration, visualization, and actionable reporting.
• Develop and evaluate AI-enabled capabilities for analysis, classification, root-cause investigation, and knowledge extraction.
• Define evaluation datasets, quality metrics, and regression tests for AI-assisted analysis tools.
• Collaborate with Algorithms, Data, and Validation teams to turn analytical findings into reliable, maintainable products.

All you need is:

• B.Sc. in Computer Science, Engineering, or a related field; relevant IDF or equivalent practical experience is also welcome.
• 3-5 years of professional Python development experience in analytics, automation, data-intensive applications, or internal tools.
• Strong hands-on experience with data-processing and visualization libraries such as Pandas, NumPy, Matplotlib, Plotly, or similar.
• Experience analyzing complex datasets and translating findings into practical metrics, tools, and engineering decisions.
• Strong understanding of data structures, algorithms, software design, debugging, testing, and maintainable code.
• Experience applying machine-learning or generative-AI capabilities in software products, analytical workflows, or developer tools.
• Familiarity with SQL, Linux, and version-control workflows; experience with AWS, ETL/data platforms, dashboards, LLM applications, agentic workflows, AI evaluation, or scikit-learn/PyTorch/TensorFlow is an advantage.