AI Engineer - Automotive AI Systems
Stellantis · Detroit, US
Job description
Job ID: 2019696
Career Area: Software Electric & Electronics
Position Type: Salaried
Location: Headquarters & Technology Center – Auburn Hills
48326, US
Date Posted: July 8, 2026
Brand: FCA Group
AI Engineer — Automotive AI Systems
AI is no longer a feature in modern vehicles — it is the vehicle. ADAS perception, voice assistants, predictive diagnostics, and intelligent infotainment are now central to how drivers experience and trust their cars. Getting these systems wrong isn’t a software bug — it’s a safety event.
We are looking for an AI Engineer who builds the frameworks, pipelines, and methodologies that stand between an AI model and a vehicle on the road. You will be the quality and safety gate for deep learning and LLM-based features across our vehicle platforms — designing the tests, the tools, and the benchmarks that give engineering teams confidence to ship.
This is a high-impact role at the intersection of AI/ML engineering and automotive system validation. Your work directly determines whether AI-driven features are safe, reliable, and ready for production.
What You Will Own:
AI Frameworks:
Design and implement end-to-end AI frameworks for deep learning models — perception, NLP, generative AI — covering accuracy, robustness, latency, and functional safety metrics across automotive deployment environments.
LLM development and validation Pipelines:
Build automated evaluation pipelines for LLM-based features including hallucination detection, response quality scoring, prompt regression testing, and adversarial input coverage. Ensure every model update is tested before it reaches a vehicle.
Automotive AI Benchmarks:
Build and curate evaluation datasets and benchmarks purpose-built for automotive AI use cases — voice command recognition, diagnostic Q&A, sensor fusion output validation, and edge-case scenario coverage.
AI-Assisted Test Generation:
Leverage LLMs to automatically generate test cases, test data, and expected-result specifications directly from system requirements — reducing manual test authoring and increasing coverage systematically.
Production Monitoring & Drift Detection:
Develop model monitoring systems that detect performance degradation, distribution shift, and drift in AI features operating in both test environments and production vehicles.
CI/CD Integration:
Embed AI model validation into existing test bench infrastructure and CI/CD pipelines — making automated regression testing a standard gate for every ML model update and software release.
Root Cause & Quality Analysis:
Apply statistical methods and ML techniques to test results to identify failure patterns, root causes, and quality trends — and translate findings into clear, actionable recommendations for engineering teams.
EOE/Disability/Veteran
At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future.
Our benefits reflects the STELLANTIS commitment to helping you reach your personal and professional goals. In addition to an environment that promotes career development, we offer benefits for a healthy lifestyle and a rewarding future, designed to take care of you and your family, in various stages of life.
As a global company, our employee packages will vary by country, customary norms and the legal entity into which you are hired.
We care about your privacy. For more information on how your personal data is processed, please read the specific Privacy Statement provided by the respective entities whose job offer you have selected.
ML/AI Work links you to the employer's original posting — always verify the details there before applying.
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