Engineering Manager - Systems Triage (Metrics & Analysis)
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About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team
The System Triage team plays a critical role in understanding how Torc's autonomous driving software performs in the real world. Through analysis of vehicle data, system performance indicators, and software quality metrics, the team helps engineering leaders identify trends, investigate complex system behaviors, and make informed decisions as we advance toward production.
Within System Triage, the Metrics & Analysis team focuses on turning large volumes of autonomous vehicle data into meaningful engineering insights. From evaluating system performance and traffic law compliance to developing metrics, dashboards, and analysis tools, the team provides visibility into the performance and maturity of our autonomous driving technology.
As the Engineering Manager for Metrics & Analysis, you'll lead a team of technical professionals, establish consistent analytical approaches, and help scale the tools and processes that support engineering decision-making. This is an opportunity to remain close to the technical work while shaping how the team operates, develops, and delivers insights across the organization.
What you'll do:
A successful candidate will have experience in people management, cross-functional collaboration, and hands-on data analysis to support system triage and software quality reporting. A solid background in metrics reporting and visualization for large-scale, safety-critical, or complex software systems is necessary to support engineering decision-making.
- Manage a small team responsible for analysis and metrics reporting, delivering value to Torc internal engineering and Torc customer-facing teams
- Prioritize and assign team workload across triage, metrics, and reporting requests from stakeholders, and remove blockers so the team can deliver
- Coach and develop team members, providing guidance on data analysis approaches, tooling practices, and career growth
- Own tracking and reporting of metrics for test escapes
- Provide system performance metrics based on data collected by our self-driving truck
- Report on software quality using concepts such as defect ratios and software heatmap viewpoints
- Develop and maintain data analysis scripts and visualization tools for efficient triage, metric reporting, and trend visualization to help the org quickly extract key learnings related to software maturity
- Combine environment observations with event logs to help identify avenues for investigation and direct root-cause analysis efforts
- Support defect tracking workflows, including monitoring bug ticket quality and the state of open defects
- Own and expand the team's analysis and metrics tooling ecosystem, identifying opportunities to automate manual reporting and reduce turnaround time on requests
- Present metrics, trends, and software quality findings to engineering leadership and cross-functional stakeholders
- Partner with triage and forensics teams to ensure metrics and tooling keep pace with a rapid integration and deployment schedule for the self-driving software stack
What you will need to succeed:
- Bachelor's degree in Computer Science, Computer Engineering, Systems Engineering, Data Science, or related technical field; experience in lieu of education
- 2-5 years of industry experience in data ana...
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About Torc Robotics
Learn more about Torc Robotics and their company culture.
Autonomous trucking company building self-driving technology for long-haul freight.
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