Sr. Specialist - AI Automation & Testing
Core
Build AI-driven automation pipelines, ML models for test prioritization/failure prediction, and NLP tools for log triage to enable rapid, reliable iteration of vehicle software and electronics.
Role type
Senior IC Machine Learning Engineer (Automotive Software Testing & Automation)
Builds
End-to-end toolchains (Code commit → build → ECU flashing → HIL testing), automated test orchestration frameworks, and AI-powered quality gates for vehicle software releases.
Domain
Automotive (Electric SUV/Truck) + Machine Learning + Embedded Systems
Deliverable
production ML models | infrastructure
Required skills
Python (advanced), SQL, Bash, ML/AI (Scikit-learn, TensorFlow/Pytorch, anomaly detection, time-series), CI/CD (Jenkins, GitLab CI, GitHub Actions), Docker, Kubernetes, Automotive protocols (CAN, LIN, FlexRay, Ethernet, UDS), Embedded systems software stacks, Log parsing/analysis, NLP pipelines.
Preferred skills
Experience with ALM/PLM tools (Codebeamer, Siemens Polarion, IBM DOORS, PTC Windchill), HIL/SIL framework development, Fleet data systems.
Technologies
Python, SQL, Bash, TensorFlow, PyTorch, Scikit-learn, Jenkins, GitLab CI, GitHub Actions, Docker, Kubernetes, CANalyzer, CANoe, n8n, Pinecone.
Responsibilities
Develop and implement end-to-end toolchains spanning code commit to vehicle/HIL testing; Build ML models for test case prioritization, failure prediction, and intelligent test selection; Implement anomaly detection on logs, CAN traces, and system telemetry; Develop NLP pipelines for automated log triage and defect classification; Integrate AI modules into CI/CD pipelines; Orchestrate workflows with Docker + Kubernetes for scalable test execution; Automate ECU flashing and OTA package generation/deployment; Build and maintain SIL/HIL frameworks and vehicle-level regression systems; Create pipelines for ingesting and analyzing vehicle telemetry and test data; Develop tools for log parsing, real-time monitoring, and alerting.
Seniority
Senior, hands-on IC