Number of Position(s): 1
Duration: 10 Weeks
Date: June 2026 to August 2026
Location: Hybrid, in Murray Hill, NJ.
EDUCATIONAL RECOMMENDATIONS
Currently a candidate for a PhD in Computer Science, Computer Systems Engineering, Math, Artificial Intelligence, or related field at an accredited school in the USA.
Responsibilities
- Design and implement state-of-the-art AI/ML decentralized systems.
- Validate and evaluate your implementation in our cutting-edge labs.
- Interface, explore, and learn from the experts.
- Expertise in deep learning fundamentals, including large language models and agent-based systems, and experience with training, deploying, and/or profiling models.
- Experience in principled systems design and development.
- Excellent communication skills, with the ability to analyze complex problems and effectively communicate findings.
- Strong publication record in top-tier AI and systems conferences.
It would be nice if you also had:
We encourage applications from candidates who have a strong foundation in one or more of the areas below, even if you don’t meet every criterion. We value diverse perspectives, innovative thinking, and complementary skills.
- Agentic AI & Large Language Models (LLMs):
Familiarity with large-scale model inference and optimization, as well as experience in LLM reasoning, prompt engineering, and resource-constrained computation.
- AI Systems Architecture & Optimization:
Experience managing GPU or accelerator resources, optimizing performance, and benchmarking across different hardware environments. A solid understanding of AI infrastructure design and inference workflows—such as KV-cache management, batching, and offloading—is beneficial.
- Compilers & Hardware–Software Co-Design:
Knowledge of computational graph representations (e.g., ONNX, MLIR, XLA, TorchScript) and model optimization frameworks (e.g., TensorRT, TVM). Experience working with heterogeneous accelerator ecosystems (e.g., TPUs, AMD ROCm GPUs) or parallelizing compilers is a plus.
- Distributed, Edge AI & Web3 Computing:
Understanding of distributed or edge inference systems (e.g., Ray Serve, DeepSpeed-Inference, vLLM), with familiarity in blockchain technologies, smart contracts, or wireless networking protocols (Wi-Fi, 3GPP, Bluetooth).
Nokia is a global leader in connectivity for the AI era. With expertise across fixed, mobile and transport networks, powered by the innovation of Nokia Bell Labs, we’re advancing connectivity to secure a brighter world.
Our recruitment process
We act inclusively and respect the uniqueness of people. Our employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law. We are committed to a culture of inclusion built upon our core value of respect.
If you’re interested in this role but don’t meet every listed requirement, we still encourage you to apply. Unique backgrounds, perspectives, and experiences enrich our teams, and you may be just the right candidate for this or another opportunity.
The length of the recruitment process may vary depending on the specific role's requirements. We strive to ensure a smooth and inclusive experience for all candidates. Discover more about the recruitment process at Nokia.
- Flexible and hybrid working schemes to balance study, work, and life
- Professional development events and networking opportunities
- Well-being programs, including Personal Support Service 24/7 - a confidential support channel open to all Nokia employees and their families in challenging situations
- Opportunities to join Nokia Employee Resource Groups (NERGs) and build connections across the organization
- Employee Growth Solutions, mentorship programs, and coaching support for your career development
- A learning environment that fosters both personal growth and professional development – for your role and beyond
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