Distinguished Engineer - Wireless Infrastructure
NVIDIA3 LocationsPosted 5 March 2026
Job Description
Nvidia is developing accelerated platforms and technologies for next generation Telecom Wireless infrastructure. We are focused on AI-RAN and Agentic Core to deliver unparalleled performance and spectral efficiency. Additionally, we are building innovative technologies for new use cases in Integrated Sensing and Communications (ISAC), Semantic Communications (SemCom) and Physical AI on a fully software defined Telco Edge infrastructure. We are looking for a motivated and energetic senior technologist for the role of Distinguished Engineer, Wireless Infrastructure. What you will be doing: Lead the technology strategy for next generation wireless infrastructure spanning systems, platforms, and software architecture. Seek and apply AI/ML approaches for key functions and pipelines of 6G radio access network (RAN). Transform the wireless core into an agentic AI based packet core architecture. Drive rapid prototyping of new algorithms to establish value proposition and benefits of GPU accelerated platforms. Work with industry ecosystem - partners and customers - to rapidly drive innovations into deployable products and solutions. Work with the industry standards and consortiums - 3GPP, AI-RAN and O-RAN - for a transformational next-G technology with AI Native approaches. Drive development of new applications in Integrated Sensing and Communications (ISAC), Semantic Communications, Physical AI at the Edge and more. Drive system architecture, requirements, design, development, performance optimizations, and benchmarks for AI-for-RAN software stack. Identify, pathfind, and develop new acceleration technologies into next generation NVIDIA hardware. What we need to see: MS or PhD in Computer Science, Electrical Engineering, or related field (or equivalent experience). 20+ years of proven industry experience. Deep technical knowledge of communication systems, communication theory, linear algebra, detection and estimation theory, baseband signal processing algorithms, and channel coding. Expertise in architecting and developing RAN applications and proven expertise in system level optimizations. Proven experience in 5G NR PHY/L1 and L2 mac-scheduler algorithms design and development. Expertise in architecting wireless core technologies including accelerated user plane function (UPF). Deep expertise in AI and Machine Learning. Proven experience in applying AI techniques into RAN (L1, L2+) pipelines. Solid foundation in statistical analysis. Strong understanding of mathematics behind RAN algorithms. Strong hands-on experience on programming languages such as Python, C/C++, Matlab. Demonstrable experience working with Telecom Service Providers deploying commercial networks is a definite plus. Ways to stand out from the crowd: Strong leadership, communication, and problem-solving skills. Demonstrated success in leading impactful innovations and converting them to commercial products. A strong body of work at the intersection of AI, Cloud and Wireless technologies. Strong exposure to wireless standardization and associated industry consortiums. Proven ability to excel in a fast paced and collaborative environment. NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our teams are rapidly growing. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 320,000 USD - 488,750 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until March 7, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in ou ... (truncated, view full listing at source)
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