Objective:
To achieve Intelligent driving system development implementation in vehicle
Task:
? Lead requirements analysis, architecture design, functional module development fautonomous driving system (e.g., perception, decision-making& planning, control), implementation in vehicle.
? Perform software-hardware integration fautomotive controllers, optimize senscalibration (e.g., Camera, LiDAR, Radar), ensure compatibility with related systems (e.g., EPS, BSM, EVCU).
? Support MIL/SIL/HIL testing, develop automated test scripts, validate ADAS functions performance.
? Analyze test data, identify system issues, drive product optimization.
? Analyze competitvehicle ADAS/AD systems, establish technical benchmarking, evaluate supplier capabilities.
? Conduct research analysis on Intelligent driving technologies to support products innovation.
Qualification:
? Education: Bachelor’s degree higher in Computer Science, Automotive Engineering, related fields.
? Skills:
Familiarity with CAN/CANFD/Automotive Ethernet protocols AUTOSAR architecture.
Knowledge of various perception sensors characteristics, GB Foreign regulations of autonomous driving
Experience in sensfusion algorithms (e.g., Kalman filtering, object tracking), SLAM/PLC, Decision-making & Planning, control algorithms (e.g., PID, MPC).
Understanding of functional safety (ISO 26262) ASPICE development processes.
? Experience: 5+ years in autonomous driving development, with ADAS L2+ /L4 mass production project experience preferred.
更新于 2025-12-30
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Principal responsibilities：
-Design, implement, maintain highly available, scalable infrastructure solutions, leveraging automation to streamline operations.
-Monitsystem performance, proactively identify potential issues, drive incident response root cause analysis.
-Collaborate with cross-functional teams (development, product, security) to integrate reliability best practices the entire software lifecycle.
-Develop manage automation scripts, CI/CD pipelines, infrastructure-as-code (IaC) frameworks to enhance efficiency reduce manual intervention.
-Optimize cloud resources, cost management, disaster recovery strategies to ensure business continuity.
Qualifications ：
-Experience: Minimum 5 years in IT operations Site Reliability Engineering, with a focus on infrastructure management system optimization.
-Technical Skills: Proficiency in operation control tools such as Ansible, Puppet, Chef, Terraform, Prometheus, Grafana, ELK Stack.
-Strong scripting skills in Python, Shell, similar languages.
Cloud Competency: Solid experience with majcloud platforms (AWS, Azure, GCP), including services like EC2, Lambda, Kubernetes, containerization.
-Problem-Solving: Proven ability to troubleshoot complex issues across distributed systems, networks, applications.
-Communication: Excellent written verbal communication skills, with the ability to collaborate effectively in a fast-paced, dynamic environment.
Preferred Qualifications:
-3+ years of dedicated experience in cloud service operations, with expertise in cloud-native architectures microservices.
-Certifications in AWS Certified Solutions Architect, Google Cloud Professional Cloud Architect, equivalent.
-Experience with service mesh technologies (e.g., Istio) observability tools (e.g., Jaeger).
-Familiarity with DevOps culture practices, including agile methodologies continuous improvement frameworks.
-Bonus: Proven experience in developing IT operation maintenance tools using Python, demonstrating the ability to automate complex workflows solve real - world problems.
更新于 2025-12-16
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