Technical Lead- AI Cockpit
Indexed description
Let’s grow together, enjoy more, and inspire each other. Work
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You will work at the intersection of AI, embedded systems, and automotive software, shaping scalable architectures while coordinating cross-functional teams to bring innovative cockpit experiences to production.
Key Responsibilities
- Define and own the end-to-end architecture for AI-driven smart cockpit systems across hardware, middleware, and application layers
- Lead design and implementation of AI/ML pipelines, model optimization, deployment, and lifecycle management
- Architect multi-model/LLM orchestration and on-device model adaptation (fine-tuning, distillation) for edge automotive deployment, including model selection, routing, and inference optimization on GPU/NPU SoCs
- Architect efficient edge AI execution, optimizing models for CPU/GPU/NPU (quantization, pruning, latency, power)
- Design hybrid edge–cloud architectures for personalization, continuous learning, and scalable feature delivery
- Integrate multimodal AI capabilities (voice, vision, sensor fusion) with real-time and safety-critical constraints
- Establish robust data pipelines, telemetry, and feedback loops, enabling continuous model validation, performance monitoring, and iterative improvement of AI capabilities in production
- Define the AI evaluation and observability framework, including model quality testing, regression checks, and production monitoring tied to release readiness
- Drive technical program execution across architecture, AI, and integration workstreams — including planning, dependencies, risk management, milestone tracking, cross-functional coordination, and stakeholder communication — to ensure on-time, high-quality production readiness
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field with 5+ years of experience in AI/ML-driven system development.
- Strong hands-on expertise in machine learning, deep learning, and AI system design, with experience deploying models on edge, embedded, or automotive platforms.
- Experience integrating AI and Generative AI/LLM-based capabilities into real-time, resource-constrained environments.
- Strong knowledge of edge AI optimization techniques (quantization, pruning, distillation) and proficiency in Python and C++, along with experience in embedded AI lifecycle management, including OTA updates and fleet telemetry.
- Hands-on experience with LLM/generative-AI orchestration and model fine-tuning/adaptation in real-time, resource-constrained environments.
- Strong understanding of cloud platforms architecture and edge–cloud orchestration, and proven ability to lead cross-functional engineering teams.
- Knowledge of automotive cockpit systems (voice assistants & personalization)
- Experience with on-device voice pipelines (ASR/TTS) and inference-serving stacks on various SoC/processors
- Exposure to user experience design for in-vehicle systems
- Strong technical leadership and architectural thinking
- Ability to balance innovation with production readiness
- Excellent communication and stakeholder management skills
- Strategic mindset with hands-on execution capability
- Passion for shaping the future of AI-defined vehicles
- AI-powered assistants that understand driver intent and context
- Personalized, self-learning cockpit experiences
- Seamless integration of infotainment, productivity, and safety features
- Next-gen human-machine interfaces (voice, gesture, multimodal AI)
By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.
BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics) Initiatives
- FIRST Robotics (For Inspiration and Recognition of Science and Technology)
- AWIM (A World In Motion)
- Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.
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