Real39m ago
(Senior / Principal) Software Test Engineer
On-SiteMinneapolis, MN, United StatesLead / Architect (8+ Yrs)Manual & Functional QA
Job Specification
Job Title – Quality Assurance Engineer I
Location – Sunnyvale, CA – Onsite
Duration – 12 Months – Possible extension
As an AV Quality Assurance Specialist, you will serve as a crucial technical bridge between real-world fleet operations, system validation engineering, and data pipeline teams. You will perform first-level analysis on complex fleet driving logs, execute initial root-cause triage on system disengagements, enrich raw driving data with structured metadata, and validate automated triage tooling. This role requires a meticulous, safety-first mindset and a passion for data-driven debugging to maintain the high fidelity of our autonomous dataset.
Data Triage & Log Analysis: Perform first-pass investigation of real-world run data, system overrides, and edge-case disengagements using specialized log visualization tools.
Metadata & Issue Tagging: Enrich intervention events with precise root-cause labels, Jira issue links, contextual tags, and diagnostic notes to accelerate dataset curation.
Issue Lifecycle Management: Support end-to-end issue tracking across identification, initial investigation, cross-functional routing, and documentation.
Tooling Feedback & QA: Test and validate automated triage scripts, bots, and internal diagnostic dashboards, delivering actionable feedback to improve tooling throughput.
Experience: Minimum 1–2+ years of technical operations, quality assurance, data triage, or software/hardware testing experience in autonomous vehicles, ADAS, robotics, aerospace, or safety-critical industries.
Data & Log Triage Skills: Demonstrated ability to perform log analysis, troubleshoot complex technical workflows, and navigate issue-tracking ecosystems (e.g., Jira, Confluence).
Scripting & Data Basics: Basic proficiency with scripting languages (e.g., Python, Bash) or database queries (SQL) for log parsing, metric verification, or data filtering.
Technical Terminology: Strong familiarity with autonomous vehicle terminology, software release workflows, and multi-sensor hardware systems.
Education: Bachelor’s degree in Engineering, Computer Science, Data Analytics, Information Systems, or equivalent technical practical experience (desired but not required).
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