Job Summary:The System Engineering discipline understands the needs of the automotive customers and translates them into requirements for the other functional disciplines (e.g. electrical, mechanical, software etc.) for implementation. In the RFI/RFQ stage, the System Engineer takes the lead in providing the technical proposals of the product to the customers. In the product development stage, the System Engineer ensures and validates that the product meets the customers’ expectations.
Duties/ Responsibilities:Testing & Validation:Define and develop system architecture and innovative concepts for automotive electronic products (including Infotainment/Cockpit, Displays, Clusters, ADAS, Gateway, Body-Control-Module (BCM) and Accessories such as Wireless Charger and USB Hub) in collaboration with platform teams of Business Units. Focus products are on Displays, Infotainment, ADAS.Drive new technology development and create innovative system solutions for Proof-of-Concept projects and RFI/RFIQ.Support Business Development in acquisition activities (RFI, RFQ) and providing customers with the best solutions in terms of technology and cost.In product development, ensure customer requirements are met in the product design discussion with various disciplines (ME, EE, SW), negotiating performance specifications with customers as required and translating customer requirements to internal requirements.Lead cross functional design reviews in system requirements, architecture concepts and system level DFMEA for the product.Support engineering teams in multi-discipline design reviews of interface specifications and design concepts, simulation results, and other module level testing results.Support engineering teams in product quality related issues, test specification definitions in system integration and system verification levels as well as manufacturing test development.
Requirements:Bachelor’s degree in electronics & electrical/computer engineering or related field, with 8 years of experience in embedded system development, preferably in automotive industry.Experience in system level architecture and platform development in automotive electronic or software systems.Experience in product development and verification of embedded systems.Experience with CAN/LIN/Ethernet and other vehicle communication network.Possess good technical writing, communication, and presentation skills.Experience in system engineering process and related tool chains.Knowledge of IATF16949, ASPICE and automotive product lifecycle is desirable.Good understanding of ISO26262 standards is preferred.Experience in cost and effort estimation for project quotations will be an added advantage.Knowledge of Real-Time Operating Systems (RTOS), QNX OS or embedded Linux will be added advantage.Knowledge of Vehicle EE Architecture is desirable.Knowledge in CarPlay, Android Auto, VoiceWillingness to travel frequently.
Personal AttributesAbility to foster good relationships inside and outside the Organization.Awareness of latest trends in automotive and relevant technology.Take initiative, customer oriented, strategic, observant, and results oriented.
Job Summary:This position involves working in a cross-functional environment with requirements definition, firmware and application development teams, and vehicle engineering. The role focuses on:Vehicle testing and tuningData collection and analysisOperational deployment of ADAS & Autonomous VehiclesRoute planning for operationsUser experience and safety analysis
Duties/ Responsibilities:Testing & Validation:Formulate comprehensive testing plans based on system requirementsDesign effective and efficient test casesExecute technical and logistical test planning through cross-functional coordinationSetup and configure testing environmentsGenerate detailed test reports
Technical Operations:ADS/ADAS feature tuning and data collectionParticipate in requirement and test case reviewsPost-test analysis and defect trackingRoot cause analysis supportDefect improvement tracking until closure
Standards & Compliance:Follow latest autonomous driving standards and regulationsStay updated with ADAS and AD industry developmentsIntroduce new testing equipment and methodologies
Requirements:Bachelor's degree in Automation, EE Engineering, Systems Engineering, Computer Science, or related engineering field3-5 years’ experience in software integration and testingStrong knowledge of Intelligent Driving System (IDS) hardware and softwareExpertise in software testing methodologies (black-box, white-box testing)Proficiency in C/C++ programmingStrong Linux OS knowledge and practical Linux programming experienceKnowledge of Automotive Bus protocols (CAN, LIN, IIC, UART)Experience with testing devices (CANoe, programmable power supply, oscilloscope)Experience in radar, USS, Lidar, vision, ADAS/APA/AD testingAutomatic testing experienceStrong communication skills and emotional intelligenceWillingness to travel as needed
Key Strengths of This RoleThis position offers excellent opportunities for professionals interested in the cutting-edge field of autonomous driving technology, combining hands-on vehicle testing with advanced system validation in a collaborative, cross-functional environment.
The role requires a blend of technical expertise, practical testing experience, and strong communication skills to ensure safety and performance standards are met for ADAS and autonomous vehicle systems.
Job summary:This role focuses on developing innovative network and communication middleware solutions for automotive electronic control units (ECUs) and embedded systems, enabling advancements in autonomous, connected, electric, and shared (ACES) vehicles.
Duties/ Responsibilities:Design and implement protocol stacks for vehicle network/communication systems (Ethernet, CAN, LIN, FlexRay, PCIe).Develop middleware solutions such as UDS, DoIP and SOME/IP.Define and document software architecture and ensure compliance with automotive standards.Innovate and lead developments in network/security technologies for ACES products.Collaborate with internal and external customers as a technical domain representative.
Requirements:Bachelor’s degree in Electronic/Computer Engineering with 5+ years of embedded system experience.Proficiency in C++ and Linux-based development environments.Expertise in network protocols (IPv4, IPv6, TCP/IP) and embedded ARM processors.Familiarity with Autosar, ROS, and real-time operating systems is an advantage.Strong problem-solving and critical-thinking skills.
Job summary:With the rapid evolution of manufacturing towards Industry 4.0, traditional rule-based AOI systems are increasingly challenged by complex products, high-mix production, and stringent quality requirements.
Our team is building next-generation AI-powered industrial AOI systems, focusing on high-precision visual AOI and edge-deployable AI solutions. The goal is to enable manufacturing equipment with robust visual perception, intelligent decision-making, and scalable deployment capability.
Key Technology Directions:Deep learning based industrial visual AOI inspectionEdge AI deployment for manufacturing equipment (Embedded System / Industrial IPC)Intelligent AOI system architecture for smart manufacturing
Duties/ Responsibilities:Multimodal AOI Algorithm Development – Design and implement deep neural networks for defect detection, visual alignment / positioning, irregular shape detection using visual cameras, structured-light, or X-ray data.Model Deployment & Performance Optimization – Deploy trained models on edge devices and integrate into manufacturing lines. Optimize inference performance (latency, throughput, memory) for real production lines.Explore few-shot and zero-shot AOI concepts and participate in system architecture design and implementation using large language models.Involved in Smart Factory AI Agents System design and implementation.
Requirements:Master’s degree or above in Computer Vision, Machine Learning, Automation, Industrial AI / AOI or related fields.Solid understanding of Solid understanding of computer vision and deep learning fundamentals.Practical experience with defect detection, segmentation, visual alignment / positioning, and common AOI algorithms.Hands-on experience with multimodal deep neural network models fine-tuning and inference optimization.Proficiency in Python and PyTorch, and Linux C/C++ programming.Preferred experience with: Industrial cameras and lighting NVIDIA TensorRT, CUDA, or edge AI optimization ROS 2 or real-time system integration Understanding of industrial communication protocols(EtherCAT, CAN), or PLC integration Experience deploying AI models in real production lines Experience with multimodal or vision-language models Exposure to intelligent factory or AI agent concepts
