Compiler Team Leader

Description About the AI Division: The AI Division is a unique and dedicated group within Ceva, driving innovation in Machine Learning and Generative AI architectures for edge devices and cloud inference. Our R&D domains span Neural Network Processors (NPU), Vision DSPs, and advanced AI algorithms for applications across smartphones, tablets, automotive, surveillance cameras and many more edge AI systems.

We combine cutting-edge hardware IP design with embedded software and system-level solutions, enabling the next generation of intelligent and energy-efficient devices. The Role Lead a team of compiler engineers responsible for Ceva's open source based toolchain and graph compiler. You will be a hands-on team leader — driving architecture decisions, guiding engineers, and delivering compiler capabilities across all Ceva hardware targets.

Our team embraces an AI-agentic development flow, leveraging AI coding agents to accelerate engineering productivity, and we are looking for a leader who champions this approach.

Responsibilities

Lead development of Ceva's open source based toolchain targeting custom DSP and NPU architectures. Drive design and delivery of graph compilation flows: transformations, operator mapping, and code generation. Champion AI-agentic development practices within the team — integrating AI coding agents into day-to-day engineering workflows.

Mentor engineers and conduct code reviews; build a high-quality engineering culture. Collaborate with hardware architecture, algorithms, and software teams globally. Own team planning, prioritization, and on-time delivery of toolchain features. Contribute hands-on to design, implementation, and performance tuning in C++ and Python.

Requirements

B.Sc. in Computer Science, Electrical Engineering, or related field. 2+ years of experience leading software development teams. 3+ years of hands-on experience in software development. Strong C++ skills; Python proficiency is a plus. Solid software engineering fundamentals. Strong communication skills; comfortable in a global, multi-site environment.

Advantages Hands-on experience with AI-agentic development — using AI coding agents (e.g. GitHub Copilot, Cursor, Claude Code) to drive and accelerate software development. Hands-on experience with LLVM/Clang — backend, instruction selection, register allocation, or code generation. Familiarity with MLIR — dialects, passes, or graph-level compiler development.

Knowledge of AI/ML frameworks and neural network execution. Experience with embedded systems, DSP or NPU architectures. M.Sc. or higher in a relevant field.