Position Summary
InterDigital is seeking a research engineer to join its Wireless Research team in the area of AI-enabled systems. This role is ideal for a recent Ph.D. graduate or Ph.D. candidate nearing completion who combines a strong theoretical grounding in AI/ML with demonstrated hands-on experience to build and evaluate working systems/prototypes.
The near-term priority for this position is to design, integrate, and evaluate end-to-end research testbeds and demonstrations for AI-enabled wireless and cellular systems. The researcher will turn research concepts into working prototypes, measurable experiments, and compelling demonstrations across 6G radio access, core/service functions, transport and application protocols, sensing, and edge/cloud compute. Over time, the role will expand into invention generation, technical publications, and standards activities, including 3GPP.
The strongest candidates bring AI/ML depth and expertise working across traditional boundaries, including RAN and core/service architecture, upper and lower layers of the protocol stack, AI algorithms and systems implementation. InterDigital is seeking a candidate motivated to grow at the intersection of wireless, AI, and end-to-end systems research. Prior 3GPP contribution experience is helpful but not required.
Key Responsibilities
- Conduct advanced research on AI-enabled mobile networks and emerging 6G systems, with emphasis on interactions among the RAN, core and service architecture, transport and application layers, edge/cloud computing, and distributed AI.
- Architect, implement, integrate, and operate end-to-end research testbeds and proof-of-concept systems using technologies such as Physics-based Simulators (e.g., CARLA, Omniverse/Isaac Sim), 5G/6G Open-Source Projects (e.g., OAI, OCUDU, Open5GS), SDRs, network emulation, edge services, digital twins, and GPU-accelerated AI platforms.
- Bridge theoretical research and practical implementation by iteratively validating new ideas through simulations and testbeds, analyzing experimental results to refine concepts, uncover new research directions, and accelerate innovation in AI-enabled wireless systems.
- Develop and evaluate AI/ML techniques for communication and networked systems, including agentic and multi-agent AI, generative AI, learning-based optimization, perception and sensor fusion, and context-aware decision making.
- Build prototypes of AI-enabled networking and distributed-intelligence concepts which may include agentic AI, semantic-aware networking, control-loop communications, Physical AI, intent-driven services, and context-aware adaptation.
- Design rigorous experiments and system metrics; evaluate performance under congestion, mobility, imperfect sensing, limited radio or compute resources, and other realistic operating conditions.
- Develop high-quality research software, simulations, automation, visualization, and instrumentation using Python, C/C++, MATLAB, Linux, AI frameworks, and reproducible software-development practices.
- Translate research results into technical reports, architecture documents, invention disclosures / patent filings, publications, demonstrators, and over time, contributions to 3GPP and other relevant standards bodies.
- Collaborate with cross-functional teams spanning wireless, video / media, AI, standards, product demonstration, and prototyping groups; share technical knowledge and help guide interns.
Required Qualifications
- Masters is a minimum with a PhD preferred, in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field.
- Strong theoretical foundation and hands-on experience in AI/ML, demonstrated through the development and evaluation of working software, simulations, prototypes, experiments, or testbeds.
- Strong foundation in wireless, mobile, networked, or cyber-physical systems, with the ability and motivation to work across RAN, core network, service, transport, application, and edge/cloud layers.
- Demonstrated ability to translate research ideas into working software, simulations, prototypes, experiments, or testbeds, rather than limiting work to conceptual analysis alone.
- Programming proficiency in Python and experience with C, C++ together with practical experience in Linux-based development environments.
- Experience with one or more machine-learning frameworks such as PyTorch, TensorFlow, or JAX.
- Ability to debug and integrate complex multi-component systems and to reason across interfaces and layers of an end-to-end architecture.
- Strong written and verbal communication skills, including the ability to explain complex technical concepts and document research results clearly.
- A collaborative, self-directed working style and the ability to balance near-term prototype delivery with longer-term research objectives.
Preferred Qualifications
- Hands-on experience with cellular research platforms such as OpenAirInterface, open-source 5G Core implementations, O-RAN components, SDRs, network emulators, or real-time wireless testbeds.
- Familiarity with 3GPP Core Network, RAN and systems architecture, including concepts such as QoS flows, network exposure, policy control, session management, user-plane functions, and edge computing. Prior standards contribution experience is helpful but not required.
- Experience with agentic AI and GenAI toolchains, including LLM APIs, retrieval-augmented generation, tool use, evaluation frameworks, vector databases, and multi-agent orchestration.
- Experience with Physical AI, robotics, autonomous systems, computer vision, multi-modal sensing, ISAC, spatial mapping, digital twins, AR/XR, CARLA, NVIDIA Omniverse, ROS, or related simulation and prototyping environments.
- Knowledge of AI, transport and application protocols used in distributed real-time systems, such as MCP, A2A, TCP/IP, UDP, QUIC, Media over QUIC, HTTP/2 or HTTP/3, gRPC, and MQTT.
- Experience with system-level or link-level simulation tools such as Sionna, ns-3, MATLAB-based simulators, or equivalent frameworks.
- Experience with cloud-native and reproducible research workflows using Git, Docker, Kubernetes, CI/CD, MLflow or similar experiment tracking, and GPU acceleration.
- Research track record demonstrated through publications, patents, standards-related work, open-source software, or major integrated prototypes.
What You Bring
- A researcher's curiosity combined with a builder's mindset.
- The ability to move comfortably between theory, code, experiments, architecture, and technical communication.
- A passion for advancing the convergence of wireless systems, AI, sensing, and distributed intelligence.
- Strong analytical and problem-solving skills, with persistence in debugging and integrating complex systems.
- A proactive, self-driven, and collaborative mindset suited to a global, cross-disciplinary research environment.
- Strong writing and communication skills, with an attention to details.
Location: Conshohocken, PA