Research Engineer / Scientist (Wireless + AI/ML)

About InterDigital InterDigital is a global research and development company focused primarily on wireless, video, artificial intelligence (“AI”), and related technologies. We design and develop foundational technologies that enable connected, immersive experiences in a broad range of communications and entertainment products and services. We license our innovations worldwide to companies providing such products and services, including makers of wireless communications devices, consumer electronics, IoT devices, cars and other motor vehicles, and providers of cloud-based services such as video streaming. As a leader in wireless technology, our engineers have designed and developed a wide range of innovations that are used in wireless products and networks, from the earliest digital cellular systems to 5G and today’s most advanced Wi-Fi technologies. We are also a leader in video processing and video encoding/decoding technology, with a significant AI research effort that intersects with both wireless and video technologies. Founded in 1972, InterDigital is listed on Nasdaq.

InterDigital is a registered trademark of InterDigital, Inc.

For more information, visit: www.interdigital.com.

Key Responsibilities

• Conduct advanced research in wireless communication systems, including PHY/MAC layers, radio architectures, networking protocols, and end-to-end system design
• Design and evaluate AI/ML-driven wireless algorithms (e.g., semantic communications, intent based and agentic AI communications, GenAI-assisted network optimization, resource allocation, edge intelligence)
• Develop and implement link-level and system-level simulations using tools such as MATLAB, Python, Sionna, or equivalent frameworks
• Build proof-of-concept prototypes (e.g., OAI, SDR, digital twins, edge AI testbeds) and validate concepts on practical platforms or testbeds
• Prototype Agentic AI and GenAI workflows for autonomous network planning, troubleshooting, orchestration, and standards-oriented research acceleration
• Explore Physical AI concepts that connect perception, sensing, wireless control, robotics/automation, and embodied AI systems over reliable low-latency networks
• Evaluate networking protocol behavior across IP, transport, application, RAN/core, edge/cloud, and distributed AI deployment environments
• Analyze and optimize system performance using theoretical and data-driven approaches
• Contribute to technical reports, publications, and patent filings
• Collaborate with cross-functional research teams across wireless, AI, standards, and prototyping groups

Required Qualifications

• Ph.D. recently completed in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field.

• Strong foundation in one or more of the following areas:

• Wireless communications
• Signal processing
• Networking
• AI/ML for communication systems

• Distributed or edge intelligence

• Solid knowledge of AI/ML techniques and their application to communication systems including GenAI, Agentic AI, foundation models, and edge learning

• Understanding of networking protocols and architectures such as TCP/IP, UDP, QUIC, HTTP/2/3, gRPC, MQTT, routing, SDN/NFV, and edge/cloud networking

• Programming proficiency in Python and MATLAB, with working knowledge of C/C++ and Linux-based development environments

• Experience with simulation and programming tools, such as:

• MATLAB, Python, C/C++, or similar scientific and systems programming languages

• Machine learning frameworks (e.g., TensorFlow, PyTorch)

• Demonstrated ability to translate theory into working simulations or prototypes

Preferred Qualifications

• Hands-on experience with:

• System-level or link-level simulators (e.g., Sionna or equivalent)
• Wireless prototyping platforms (e.g., SDRs, OAI testbeds, or real-time systems)
• Generative AI and agent toolchains, including LLM APIs, RAG pipelines, vector databases, prompt/evaluation frameworks, and autonomous agent orchestration
• Physical AI, robotics, sensing, perception, control, embodied AI, or cyber-physical systems integrated with wireless connectivity

• MLOps and reproducible AI workflows using Docker, Kubernetes, MLflow, CI/CD, and GPU acceleration (CUDA where applicable)

• Research track record including publications, patents, or technical contributions
• Familiarity with cellular standards (4G/5G/6G evolution)
• Experience in AI-native wireless systems, edge intelligence, or s…