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.
About the Role:
As a senior compiler engineer, you will own the design and development of Ceva’s open source based toolchain and graph compiler. You will drive technical solutions end-to-end, deliver compiler capabilities across all Ceva hardware targets, and help mentor engineers. Our team embraces an AI-agentic development flow, leveraging AI coding agents to accelerate engineering productivity, and we are looking for engineers who champion this approach.
Responsibilities:
Design and develop 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 — integrating AI coding agents into day-to-day engineering workflows.
Own complex components end-to-end, from architecture and design through implementation and delivery.
Provide technical guidance and mentorship to engineers; conduct code reviews.
Collaborate with hardware architecture, algorithms, and software teams globally.
Analyze and optimize toolchain output for performance and correctness across Ceva processor families.
Requirements
B.Sc. in Computer Science, Electrical Engineering, or related field.
5+ years of hands-on experience in software development.
Proven ability to own and deliver complex software components independently.
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.
