Pay Growth
?
out of 5
Not enough data
Not enough info to score pay or growth
Technical Lead- Automotive AI Cockpit
Job
Bosch Group
Plymouth, MI (In Person)
Full-Time
Review key factors to help you decide if the role fits your goals.
Job Security
?
out of 5
Not enough data
Calculating job security score...
Total Score
99
out of 100
Average of individual scores
Skill Insights
Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.
Job Description
Company DescriptionAt Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people's lives. Our areas of activity are every bit as diverse as our outstanding Bosch teams around the world. Their creativity is the key to innovation through connected living, mobility, or industry.
Let's grow together, enjoy more, and inspire each other. Work #LikeABosch
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 ResponsibilitiesDefine and own the end-to-end architecture for AI-driven smart cockpit systems across hardware, middleware, and application layersLead design and implementation of AI/ML pipelines, model optimization, deployment, and lifecycle managementArchitect 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 SoCsArchitect efficient edge AI execution, optimizing models for
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.
Preferred QualificationsKnowledge of automotive cockpit systems (voice assistants & personalization)Experience with on-device voice pipelines (ASR/TTS) and inference-serving stacks on various SoC/processorsExposure to user experience design for in-vehicle systemsKey CompetenciesStrong technical leadership and architectural thinkingAbility to balance innovation with production readinessExcellent communication and stakeholder management skillsStrategic mindset with hands-on execution capabilityPassion for shaping the future of AI-defined vehiclesWhat You'll Work OnAI-powered assistants that understand driver intent and contextPersonalized, self-learning cockpit experiencesSeamless integration of infotainment, productivity, and safety featuresNext-gen human-machine interfaces (voice, gesture, multimodal AI)Additional InformationAll your information will be kept confidential according to EEO guidelines. 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
- Reinvent yourself: At Bosch, you will evolve.
- Discover new directions: At Bosch, you will find your place.
- Balance your life: At Bosch, your job matches your lifestyle.
- Celebrate success: At Bosch, we celebrate you.
- Be yourself: At Bosch, we value values.
- Shape tomorrow: At Bosch, you change lives.
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 ResponsibilitiesDefine and own the end-to-end architecture for AI-driven smart cockpit systems across hardware, middleware, and application layersLead design and implementation of AI/ML pipelines, model optimization, deployment, and lifecycle managementArchitect 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 SoCsArchitect 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 deliveryIntegrate multimodal AI capabilities (voice, vision, sensor fusion) with real-time and safety-critical constraintsEstablish robust data pipelines, telemetry, and feedback loops, enabling continuous model validation, performance monitoring, and iterative improvement of AI capabilities in productionDefine the AI evaluation and observability framework, including model quality testing, regression checks, and production monitoring tied to release readinessDrive 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 readinessQualificationsRequired QualificationsBachelor'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.
Preferred QualificationsKnowledge of automotive cockpit systems (voice assistants & personalization)Experience with on-device voice pipelines (ASR/TTS) and inference-serving stacks on various SoC/processorsExposure to user experience design for in-vehicle systemsKey CompetenciesStrong technical leadership and architectural thinkingAbility to balance innovation with production readinessExcellent communication and stakeholder management skillsStrategic mindset with hands-on execution capabilityPassion for shaping the future of AI-defined vehiclesWhat You'll Work OnAI-powered assistants that understand driver intent and contextPersonalized, self-learning cockpit experiencesSeamless integration of infotainment, productivity, and safety featuresNext-gen human-machine interfaces (voice, gesture, multimodal AI)Additional InformationAll your information will be kept confidential according to EEO guidelines. 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) Future sponsorship for work authorization not available. Equal Opportunity Employer, including disability / veterans
- Bosch adheres to Federal, State, and Local laws regarding drug-testing.