About Ceva SDT

Ceva's Software Development Tools group builds compilers, tools, and embedded software for AI, Vision, Mobile Broadband, and NB-IoT processors. We work across the full stack — from LLVM-based toolchains to MLIR graph compilers — enabling customers to get the best out of Ceva silicon.

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.

Why Ceva SDT?

Work on toolchain technology deployed in millions of AI devices worldwide. Join a technically driven team at the forefront of AI-agentic development, where your work directly shapes how software runs on silicon.

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.