Senior Edge AI & Robotics Engineer (f-m-d)

APTIV INDIA; Wuppertal; On-site; EUR 110,000 - 160,000; Full time

Job summary

Aptiv is seeking a Senior Edge AI & Robotics Engineer to lead deployment, optimization, and scaling of AI workloads on embedded and edge computing platforms. You will work at the intersection of AI, embedded systems, software architecture, and heterogeneous computing for real-world constraints in performance, latency, power, memory, reliability, and safety.

Experience with robotics or autonomy is valued. Strong C/C++ and Python skills, Linux-based development, and hands-on model deployment are

Qualifications

• Master's degree or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Robotics, Computer Engineering, or a related discipline.
• 5+ years of experience developing and deploying AI/ML workloads on embedded or edge computing platforms.
• Experience with NVIDIA Jetson, Qualcomm, TI, NXP, Renesas, AMD, Intel, or similar embedded AI platforms.
• Expert level proficiency in C/C++ and Python.
• Hands-on experience with AI model deployment and optimization on resource-constrained systems.
• Deep understanding of AI inference frameworks, model optimization techniques, and heterogeneous compute architectures.
• Experience with Linux-based embedded systems and cross-compilation workflows.
• Strong understanding of system-level performance optimization, profiling, and debugging.
• Ability to communicate complex technical concepts effectively across multidisciplinary teams.

Responsibilities

• Design, develop, and deploy AI/ML solutions on embedded and edge computing platforms.
• Optimize inference performance across CPU, GPU, NPU, DSP, FPGA, and heterogeneous SoC architectures.
• Build scalable Edge AI software pipelines supporting computer vision, sensor fusion, multimodal AI, and real-time decision-making applications.
• Deploy and optimize models using frameworks such as TensorRT, ONNX Runtime, OpenVINO, TFLite, TVM, or equivalent technologies.
• Drive model optimization through quantization, pruning, compression, distillation, and hardware acceleration techniques.
• Develop reusable software frameworks and deployment workflows that can scale across multiple product lines and hardware platforms.
• Develop high-performance software in C/C++ for embedded and edge AI applications.
• Optimize performance, memory utilization, power consumption, startup time, and system throughput.
• Design software architectures that enable portability across different hardware platforms and operating environments.
• Work with Linux-based embedded systems, RTOS environments, containerization technologies, and cross-compilation toolchains.
• Collaborate closely with hardware teams to influence compute architecture, accelerator selection, sensor integration, and platform trade-offs.
• Define benchmarking, profiling, and validation strategies for AI applications deployed at the edge.
• Establish performance, reliability, robustness, and scalability metrics.
• Support the transition from research prototypes to production-grade software solutions.
• Develop automated testing, integration, and deployment workflows and CI/CD pipelines.
• Collaborate with safety, systems, and quality teams to support safety-critical and mission-critical deployments.
• Contribute to Edge AI solutions deployed in robotics, autonomous systems, industrial automation, and intelligent machines.
• Support integration with robotics middleware and autonomy stacks where applicable.
• Collaborate with robotics teams on perception, localization, planning, and control powered by Edge AI.

Skills

C/C++

Python

Embedded systems

Linux

AI/ML deployment

ROS 2

Education

Master's or PhD in Computer Science / Electrical Engineering / AI / Robotics

Tools

TensorRT

ONNX Runtime

OpenVINO

TFLite

TVM

NVIDIA Jetson

Job description

Aptiv is a global technology leader with more than 200,000 employees across 48 countries. We develop advanced software, compute platforms, and intelligent systems that enable autonomous driving, advanced driver-assistance systems (ADAS), connected mobility, and intelligent infrastructure. Aptiv technology is embedded in millions of vehicles worldwide and powers some of the industry's most advanced automotive platforms.

As part of our expansion into Robotics and Adjacent Markets, Aptiv is developing scalable Edge AI and intelligent computing platforms for autonomous mobile robots (AMRs), drones, industrial automation, and next-generation intelligent machines. These platforms combine edge AI, heterogeneous compute, embedded software, safety-critical systems, and cloud-connected architectures to deliver real-world autonomy and decision-making at the edge.

As a Senior Edge AI & Robotics Engineer , you will serve as a hands‑on technical leader focused on the deployment, optimization, and scaling of AI workloads on embedded and edge computing platforms. You will work at the intersection of AI, embedded systems, software architecture, and heterogeneous computing, enabling production‑ready AI solutions that operate under real‑world constraints for performance, latency, power, memory, reliability, and safety. Experience with robotics, autonomy is highly valued but not required.

Key Responsibilities

Edge AI Platform Development

• Design, develop, and deploy AI/ML solutions on embedded and edge computing platforms.
• Optimize inference performance across CPU, GPU, NPU, DSP, FPGA, and heterogeneous SoC architectures.
• Build scalable Edge AI software pipelines supporting computer vision, sensor fusion, multimodal AI, and real‑time decision‑making applications.
• Deploy and optimize models using frameworks such as TensorRT, ONNX Runtime, OpenVINO, TFLite, TVM, or equivalent technologies.
• Drive model optimization through quantization, pruning, compression, distillation, and hardware acceleration techniques.
• Develop reusable software frameworks and deployment workflows that can scale across multiple product lines and hardware platforms.

Embedded Systems & Software Engineering

• Develop high-performance software in C/C++ for embedded and edge AI applications.
• Optimize performance, memory utilization, power consumption, startup time, and system throughput.
• Design software architectures that enable portability across different hardware platforms and operating environments.
• Work with Linux-based embedded systems, RTOS environments, containerization technologies, and cross‑compilation toolchains.
• Collaborate closely with hardware teams to influence compute architecture, accelerator selection, sensor integration, and platform trade‑offs.

Edge AI Validation & Production Readiness

• Define benchmarking, profiling, and validation strategies for AI applications deployed at the edge.
• Establish performance, reliability, robustness, and scalability metrics.
• Support the transition from research prototypes to production‑grade software solutions.
• Develop automated testing, integration, and deployment workflows and CI/CD pipelines.
• Collaborate with safety, systems, and quality teams to support safety‑critical and mission‑critical deployments.

Robotics & Intelligent Systems (Preferred)

• Contribute to Edge AI solutions deployed in robotics, autonomous systems, industrial automation, and intelligent machines.
• Support integration with robotics middleware and autonomy stacks where applicable.
• Collaborate with robotics teams on perception, localization, planning, and control powered by Edge AI.

Basic Qualifications

• Master's degree or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Robotics, Computer Engineering, or a related discipline.
• 5+ years of experience developing and deploying AI/ML workloads on embedded or edge computing platforms.
• Experience with NVIDIA Jetson, Qualcomm, TI, NXP, Renesas, AMD, Intel, or similar embedded AI platforms.
• Expert level proficiency in C/C++ and Python.
• Hands‑on experience with AI model deployment and optimization on resource‑constrained systems.
• Deep understanding of AI inference frameworks, model optimization techniques, and heterogeneous compute architectures.
• Experience with Linux-based embedded systems and cross‑compilation workflows.
• Strong understanding of system‑level performance optimization, profiling, and debugging.
• Ability to communicate complex technical concepts effectively across multidisciplinary teams.

Preferred Qualifications

• Experience with ROS 2, DDS, robotics middleware, or autonomous systems development.
• Experience deploying computer vision, multimodal AI, perception, or sensor‑fusion applications.
• Background in robotics, drones, AGVs/AMRs, industrial automation, or intelligent machines.
• Experience with Docker containers, CI/CD pipelines, DevOps automation, and/or MLOps practices for deploying and managing machine learning solutions in production environments.