Build the Metrics Visualization Hub (Full-Stack): Design and ship an end-to-end web application — front-end dashboards through back-end services — that makes autonomous-vehicle product metrics, route analytics, and pipeline health easy to explore for engineering and operations teams.
Deliver Low-Latency Data Access: Build a caching and pre-aggregation layer to reduce latency in result fetching
Optimize the Metrics Calculation Pipeline: Profile, refactor, and scale the back-end pipelines that compute product metrics, operation summaries, and route extractions — improving throughput, controlling cost, and strengthening the correctness of derived measures.
Develop the Metrics Validation Process: Build and automate validation tooling that cross-checks pipeline outputs against source-of-truth references, flags discrepancies, and gates bad data before it reaches downstream consumers — turning manual triage into a repeatable, alert-driven workflow.
Full-Stack Web Development: Strong proficiency building modern web applications end-to-end — front-end frameworks (e.g., React/TypeScript) and back-end services/APIs (e.g., Python/FastAPI) — with an eye for clean, responsive, data-rich interfaces.
Backend & Data Pipeline Development: Solid programming fundamentals (e.g., Python, SQL) and experience designing, building, and maintaining data processing pipelines and the services.
Performance & Scalability: Ability to analyze code, system architecture, and data pipelines to improve execution speed and resource efficiency, including caching and pre-aggregation strategies for low-latency data access.
Working with Large Datasets: Experience handling and processing high volumes of structured and time-series data, with strong SQL skills and familiarity with relational and/or columnar databases.
Big Data Processing: Hands-on experience with distributed processing frameworks such as PySpark for large-scale data pipelines.
Domain Exposure: Familiarity with autonomous vehicles, robotics, or other sensor/telemetry-heavy data environments.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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