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About Ceva:
Ceva is the leader in innovative silicon and software IP solutions that enable smart edge products to connect, sense, and infer data more reliably and efficiently. We help the world’s leading semiconductor companies and original equipment manufacturers turn great ideas into extraordinary products. We create and license technology that powers the newest generation of smart edge devices, and provide innovative silicon and software IP solutions for artificial intelligence, computer vision, audio processing, sensor fusion, 5G and satellite communication, and wireless connectivity. With more than 20 billion devices shipped, Ceva is making the future brighter for people all around the world.
About the Role:
In this role, you will develop software techniques to realize and accelerate machine learning algorithms in the fields of high-performance embedded computing. You will work on latest technologies in machine learning areas as well as Computer Vision domains. You will have the opportunity to become an expert in embedded software, scientific computing, data processing, performing in-depth analysis and optimization to ensure and promote the Ceva solutions in machine learning area.
Responsibilities:
Develop software tools and applications in the machine learning field for embedded computing. Create and optimize core parallel software algorithms and data structures.
Analyze, optimize and debug complex solutions. collaborate globally with multiple software and hardware teams, system architects and field application engineers.
Work closely with Ceva customers to analyze requirements and provide prompt support when needed.
The role includes periodic travel to customer sites within China and occasional international travel, including trips to Israel, for collaboration, training, and project alignment.
Candidates should be comfortable working in a fast-paced, result-driven environment and willing to take ownership beyond standard working hours when needed.
RequirementsRequirements:
• B.Sc/M.Sc. in Software Engineering, Computer Science, or related technical field from a leading university
• 3-6 years of experience in software development in leading companies
• Experience in fields such as AI, LLMs, computer vision. Video encoding/decoding, imaging – advantage
• Strong knowledge of C/C++
• Strong Knowledge of Python
• Strong mathematical fundamentals
• Good communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills
Advantages:
• Familiar with MLIR compiler for NPU
• Familiar with memory analysis (Macro tile and Micro tile) for NPU
Skills Required
- B.Sc/M.Sc. in Software Engineering, Computer Science, or related technical field from a leading university
- 3-6 years of experience in software development in leading companies
- Strong knowledge of C/C++
- Strong Knowledge of Python
- Strong mathematical fundamentals
What We Do
Ceva powers the Smart Edge, bridging the digital and physical worlds to bring AI-driven products to life. Our Ceva AI fabric portfolio of silicon and software IP enables devices to Connect, Sense, and Infer – the essential capabilities for the intelligent edge. From 5G, cellular IoT, Bluetooth, Wi-Fi, and UWB connectivity to scalable Edge AI NPUs, AI DSPs, sensor fusion processors and embedded software, Ceva provides the foundational IP for devices that connect, understand their environment, and act in real time. With more than 20 billion devices shipped and trusted by 400+ customers worldwide, Ceva is the backbone of today’s most advanced smart edge products – from AI-infused wearables and IoT devices to autonomous vehicles and 5G infrastructure. Our differentiated solutions deliver seamless integration into existing design flows, total flexibility to combine solutions based on design needs and ultra–low–power performance in minimal silicon footprint, helping customers accelerate development, reduce risk, and bring innovative products to market faster. As technology evolves toward Physical AI, Ceva’s IP portfolio lays the foundation for systems that are always connected, contextually aware, and capable of intelligent, real-time decision-making.
