Member of Technical Staff - Cloud & Edge AI Platforms

Aptiv

About The Position

About the Role We are looking for a Member of Technical Staff (MTS) to play a key technical leadership role in designing and advancing Wind River’s next‑generation intelligent systems platform. This position is ideal for an engineer who thrives at the intersection of cloud‑native infrastructure, edge computing, and AI/ML systems—and who wants to shape the architecture and implementation of distributed AI platforms used in mission‑critical environments. What You’ll Do Architecture & Platform Development Design and implement core components of Wind River’s cloud‑to‑edge AI platform, including orchestration layers, data pipelines, and model lifecycle management. Develop scalable, modular, and secure software architectures for distributed AI workloads across heterogeneous edge environments. Build cloud‑native services and APIs that integrate seamlessly with Wind River Studio and edge operating systems (VxWorks, Linux). Contribute to architectural decisions involving microservices, containerization, service mesh, and hybrid cloud deployments. AI/ML Infrastructure & Optimization Implement systems for model deployment, versioning, CI/CD for AI, and real‑time inference pipelines. Integrate AI frameworks (TensorFlow, PyTorch, ONNX Runtime, TensorRT) into cloud-edge workflows. Optimize inference performance across diverse hardware accelerators (GPU, NPU, FPGA, VPU). Performance, Reliability & Security Ensure platform components meet stringent requirements for determinism, safety, and reliability in mission-critical industries. Implement security best practices for distributed AI, including model protection, secure communication, and data integrity. Profile, tune, and optimize system performance across cloud and edge environments. Collaboration & Technical Leadership Work closely with architects, senior engineers, and product managers to translate platform vision into robust implementations. Mentor junior engineers and contribute to engineering best practices, design reviews, and technical roadmaps. Engage with customers and partners to understand requirements and support advanced solution development. Contribute to open‑source initiatives and represent Wind River in technical communities when appropriate. What You Bring Technical Depth 8+ years of experience in software engineering, distributed systems, cloud platforms, or embedded systems. Strong hands‑on experience with cloud‑native technologies (Kubernetes, containers, microservices). Solid understanding of AI/ML infrastructure, model deployment, and edge inference optimization. Proficiency in C/C++, Python, and modern DevOps practices (CI/CD, GitOps). Experience with Linux‑based systems, real‑time environments, or embedded platforms. Familiarity with cloud platforms (AWS, Azure, GCP) and hybrid cloud architectures. AI/Edge Exposure Experience in mission-critical or safety-critical domains (automotive, aerospace, industrial, medical). Knowledge of virtualization technologies (KVM, ACRN, hypervisors) and secure partitioning. Background in distributed AI, federated learning, or edge-to-cloud orchestration frameworks. Contributions to open‑source cloud, AI, or embedded systems projects. Ways of Working A strong engineering mindset with the ability to design, implement, and optimize complex distributed systems. A passion for building intelligent, resilient platforms that power the next generation of autonomous and connected systems. The ability to collaborate effectively across teams and influence technical direction. Curiosity, initiative, and a drive to push the boundaries of cloud‑edge AI integration. Why This Role Matters This role is critical to translating platform vision into scalable, production-ready systems. As an MTS, you will contribute deep technical expertise, lead complex engineering initiatives, mentor teams, and collaborate across product, research, and customer organizations to deliver scalable, secure, and high‑performance cloud‑to‑edge AI capabilities. Privacy Notice - Active Candidates: https://www.aptiv.com/privacy-notice-active-candidates Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law. Aptiv is a global technology company that develops safer, greener and more connected solutions enabling the future of mobility. Headquartered in Dublin, Aptiv has approximately 180,000+ employees and operates 12 technical centers, as well as manufacturing sites and customer support centers in 44 countries. Visit aptiv.com. Please review Aptiv's privacy policy by following this link: https://www.aptiv.com/privacy-notice

Requirements

8+ years of experience in software engineering, distributed systems, cloud platforms, or embedded systems.
Strong hands‑on experience with cloud‑native technologies (Kubernetes, containers, microservices).
Solid understanding of AI/ML infrastructure, model deployment, and edge inference optimization.
Proficiency in C/C++, Python, and modern DevOps practices (CI/CD, GitOps).
Experience with Linux‑based systems, real‑time environments, or embedded platforms.
Familiarity with cloud platforms (AWS, Azure, GCP) and hybrid cloud architectures.

Nice To Haves

Experience in mission-critical or safety-critical domains (automotive, aerospace, industrial, medical).
Knowledge of virtualization technologies (KVM, ACRN, hypervisors) and secure partitioning.
Background in distributed AI, federated learning, or edge-to-cloud orchestration frameworks.
Contributions to open‑source cloud, AI, or embedded systems projects.

Responsibilities

Design and implement core components of Wind River’s cloud‑to‑edge AI platform, including orchestration layers, data pipelines, and model lifecycle management.
Develop scalable, modular, and secure software architectures for distributed AI workloads across heterogeneous edge environments.
Build cloud‑native services and APIs that integrate seamlessly with Wind River Studio and edge operating systems (VxWorks, Linux).
Contribute to architectural decisions involving microservices, containerization, service mesh, and hybrid cloud deployments.
Implement systems for model deployment, versioning, CI/CD for AI, and real‑time inference pipelines.
Integrate AI frameworks (TensorFlow, PyTorch, ONNX Runtime, TensorRT) into cloud-edge workflows.
Optimize inference performance across diverse hardware accelerators (GPU, NPU, FPGA, VPU).
Ensure platform components meet stringent requirements for determinism, safety, and reliability in mission-critical industries.
Implement security best practices for distributed AI, including model protection, secure communication, and data integrity.
Profile, tune, and optimize system performance across cloud and edge environments.
Work closely with architects, senior engineers, and product managers to translate platform vision into robust implementations.
Mentor junior engineers and contribute to engineering best practices, design reviews, and technical roadmaps.
Engage with customers and partners to understand requirements and support advanced solution development.
Contribute to open‑source initiatives and represent Wind River in technical communities when appropriate.