Member of Technical Staff - Cloud & Edge AI Platforms

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.

• 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.

• 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.

• 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.

• 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.