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Provide functional safety systems engineering for compute platform components in autonomous trucks. Lead safety design discussions, derive safety requirements, perform HARA/FTA/FMEA/DFA analyses, maintain requirements in DOORS and Jama, and develop verification/validation strategies with cross-functional teams and suppliers.

The Senior ML Engineer will architect data pipelines, develop classification algorithms, manage data integration, and mentor team members in a cross-functional setting.

Lead design and delivery of cloud-based pipelines that convert multi-sensor AV logs into VLM/VLA training datasets. Build VLM-assisted auto-labeling, generate language-grounded reasoning labels, mine rare scenarios, define dataset schemas and quality metrics, and operationalize continuous dataset delivery. Mentor engineers and partner with model teams to improve downstream model performance using distributed compute and scalable MLOps.

Lead Requirements and Safety workstreams as a Technical Product Manager: prioritize needs, build cross-functional plans, define and verify acceptance criteria, manage dependencies, risks, and change, and report roadmap status to drive timely execution toward product milestones.

Develop and maintain real-time C++ vehicle mission interface software enabling Mission Control, Remote Assistance, route management, telemetry, and vehicle status monitoring. Translate system requirements into scalable architectures, contribute to simulation and testing, integrate cross-functional systems, mentor peers, and support safety-critical automotive development and validation practices.

The Senior Machine Learning Engineer will develop end-to-end ML systems connecting perception inputs to driving behavior, enhance model performance, and mentor juniors.

The Software Engineer II will develop C++ applications for real-time embedded systems, lead design efforts, mentor junior engineers, and manage the software development lifecycle in an Agile environment.

Develop and deploy machine learning solutions for autonomous truck applications: EDA, deep learning model development, embedded deployment, data ingestion/curation, analytics, visualization, technical leadership, and process improvement across manufacturing and business domains.

Build and maintain cloud-based Mission Control web applications to support autonomous trucks. Own full development lifecycle: requirements, design, coding, testing, deployment automation. Collaborate in Agile teams to implement features, uphold best practices, and refine scalable frameworks for production-ready applications.

Build and maintain cloud-based web applications for Mission Control supporting autonomous truck missions. Own full SDLC from requirements and design to coding, testing, deployment automation, and production support. Work with TypeScript/JavaScript, Python, React, AWS, Terraform, and observability tools in an Agile, cross-functional team.