Staff AI Platform Evaluation Software Engineer - Autonomous Vehicles

• Improve learning velocity from failures

• Reduce reliability escapes

• Increase confidence in production readiness

• Correctly detected and interpreted

• Consistently categorized and de-duplicated

• Rapidly mapped to the right owners and solution space

• Own the AV software reliability triage framework for the on-vehicle / AV platform stack defining how failures from simulation CI HIL/SIL and on-road validation are detected grouped and escalated into actionable tickets and insights.

• Perform deep debugging and root-cause analysis across:

• AV platform and framework code

• Perception / planning / control software integrations

• ML pipelines and model rollouts

• Vehicle compute and hardware interfaces (sensors ECUs networks)
  Connecting failure symptoms (logs time-series traces) to clear solution paths and corrective actions.

• Design and evolve automated triage mechanisms and reliability taxonomies that:

• Improve regression detection and signal-to-noise ratio

• Identify flaky tests and intermittent platform issues

• Enable consistent failure classification across teams and releases

• Build and govern reliability data pipelines for AV software:

• Ingest logs metrics traces and test results across CI simulation and vehicle runs

• Compute stability trends recurrence patterns and systemic risks

• Provide dashboards and views that support day-to-day triage and release readiness reviews

• Apply AI / ML to reliability triage for example:

• Clustering and de-duplicating failures across large-scale test runs

• Learning-based suggestions for ownership component mapping and likely root causes

• LLM-powered summaries of complex failure scenarios for engineers and leadership

• Translate reliability findings into decision-grade communication :

• Influence prioritization of bugs vs. technical debt vs. feature work

• Provide input to go/no-go decisions and safety/release governance

• Create clear narratives and visuals for engineering safety and leadership audiences

• Strong proficiency in Python for automation log analysis data processing and reliability tooling.

• Proficiency in SQL for querying reliability and test data building views and supporting dashboards.

• Proven experience with CI/CD systems (e.g. GitHub Actions Jenkins GitLab CI or equivalent) used to run automated tests for complex software systems.

• Hands-on experience implementing ETL/ELT pipelines for reliability quality or system health monitoring (e.g. ingesting logs/metrics from test runs building reliability datasets).

• Solid understanding of software reliability engineering concepts including:

• Regression tracking

• Flakiness detection and management

• Failure classification and de-duplication

• Release criteria and quality gates for software

• Strong analytical and cross-stack debugging skills in large-scale distributed or real-time software systems ideally with C++ and/or Python-based services .

• Experience integrating simulation HIL/SIL or system-level AV/robotics test signals into automated analysis workflows.

• Track record of effective cross-functional collaboration with software engineering QA test platform and systems teams .

• Ability to operate autonomously in high-ambiguity safety-critical environments driving clarity and decisions from noisy data.

• Excellent written and verbal communication skills for presenting data-driven reliability insights to engineers and technical leadership.

• Bachelor's Master's or PhD in Computer Science Electrical/Computer Engineering Robotics or a related field - or equivalent software-focused experience .

• Experience with reliability governance in ML-based or AV systems including:

• Model rollout policies

• Guardrails / kill-switches

• Shadow or A/B validation strategies

• Familiarity with reliability methodologies (e.g. FMEA reliability growth analysis MTBF trends) applied to software and integrated AV platforms.

• Knowledge of AV / ADAS software architectures including:

• Perception / localization / planning / control pipelines

• On-vehicle platform software middleware and simulation-to-road validation loops

• Experience building reliability or analytics pipelines in cloud environments (AWS GCP Azure) to support AV software validation at scale.

• Familiarity with observability and visualization tools (e.g. Grafana Superset Power BI or similar) for reliability dashboards and on-call / triage workflows.

• Experience using Jira GitHub Projects or similar tools to design reliability triage workflows routing SLAs and dashboards.

• Experience applying AI / ML or LLMs to:

• Log analysis and anomaly detection

• Failure clustering and root-cause suggestion

• Automated summarization of complex test outcomes

What We Do

At General Motors our vision is to create a world with Zero Crashes Zero Emissions and Zero Congestion. We wholeheartedly embrace the responsibility to lead the change that will make our world better safer and more equitable for all. Our industry and company are undergoing a once-in-a-lifetime technological transformation which is reshaping our approach to technology and innovation. We are expanding our horizons through new technology platforms and driving innovations that deliver exceptional value to our customers.

Why Work With Us

At General Motors our purpose is to pioneer the innovations that move and connect people to what matters. We’re driving the world forward together. We’re building vehicle software alongside its hardware hands-free driving that will lead to autonomy and EVs that charge your home for an all-electric future.

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