Associate Engineer - Edge AI

ABOUT WIND RIVER

Wind River is a global leader in delivering software for mission-critical intelligent systems. For more than four decades, the company has been an innovator and pioneer, powering billions of systems that require the highest levels of security, safety, and reliability.

Wind River helps customers across automotive, aerospace, defense, industrial, medical, and telecommunications industries solve complex technology challenges on their journey toward the new intelligent machine economy. The company's software powers generation after generation of the safest, most secure systems in the world. Examples include playing a key role in NASA space missions such as Artemis I, the James Webb Space Telescope, and multiple Mars rovers. We've achieved recent 5G milestones including the world's first successful 5G data session with Verizon and building one of the largest Open RAN networks in the world with Vodafone.

The company has received industry recognition for its technology innovation and leadership, and for its workplace culture, including global Great Place to Work certification and being named a "Top Workplace" for ten consecutive years. If you want to be part of a unique culture where the lived experience is based on our cultural attributes of growth mindset, customer-focus, and diversity, equity, inclusion & belonging, come join us and help advance the future software defined world.

About the Role

You will help build and sustain the platform alongside Windriver team that runs AI Systems on the device - a Rust-based system that manages AI application lifecycles across a heterogeneous fleet of edge hardware. This is a hands-on role on hard systems problems: constrained compute, cross-architecture builds, OTA updates, and production-grade observability. You will start with well-scoped pieces of the platform, with mentoring and code review from senior engineers, and grow into larger areas of ownership. We expect you to make AI tooling a core part of how you work from day one.

What You'll Do

• Implement and test components of the edge packaging and runtime system - a containerless / OCI-based approach to shipping AI Systems to heterogeneous devices
• Contribute to the on-device orchestration platform and help support OTA update and lifecycle management for fielded devices
• Measure and improve inference and resource usage on constrained CPU/GPU/NPU hardware
• Work on cross-compilation and CI/CD pipelines for reproducible, secure multi-architecture builds
• Help integrate the device fleet with the cloud control plane and backend services (REST/gRPC, OpenAPI, MQTT)
• Reproduce, diagnose, and fix defects on real hardware, and turn what you learn into tests
• Use agentic AI coding tools daily for implementation, refactoring, review, and debugging - and build real judgment about where they help and where they don't
• Take part in the team's AI-assisted engineering practice: working patterns, guardrails, and what stays human-owned.
• Keep the codebase and its documentation in a state that people can work in effectively.

• Degree in Computer Science, Machine Learning, or a related field (or equivalent practical experience), and 1 to 3 years of professional software engineering experience.
• Working proficiency in Rust or Python, and willingness to learn the other (C/C++ exposure is a plus)
• Hands-on experience using agentic AI tools in the software development workflow - AI coding assistants and agents for implementation, refactoring, and review - and an emerging point of view on their limits.
• Comfortable on Linux and with Git-based workflows
• Experience with embedded Linux
• Systematic debugging instincts: you narrow problems down rather than guess
• Clear written communication and the ability to work with a team distributed across the NA, Europe, and India
• Genuine curiosity about the full stack - cloud, edge, and web/backend - and about how the networking stack works.

• Exposure to embedded Linux or systems programming
• ML frameworks or inference runtimes (PyTorch, ONNX, TensorRT, TFLite, OpenVINO) and the realities of running models on device
• NPU/GPU hardware such as Jetson, Qualcomm, Hailo, or Ambarella
• GenAI/LLM tooling or RAG pipelines; multi-arch builds; a major cloud provider (AWS, GCP, Azure); GitLab CI.

Aptiv began leading the way in software and systems technologies years ago. With our rich history as a foundation, our dedicated team is uniquely capable of driving the future of mobility.

As the only provider of an integrated vehicle brain and nervous system, Aptiv works with our customers to create software-defined vehicles and solve mobility’s toughest challenges in autonomous driving, vehicle electrification, advanced safety, and much more. We believe that mobility has the power to change the world. At Aptiv, we’re delivering the software capabilities, advanced computing platforms and networking architecture that make mobility work.