Number of Position(s): 2
Duration: 10 Weeks
Date: June - August, 2026
Location: On-site, in Murray Hill, New Jersey.
Education Recommendations
Eligible candidates should currently be pursuing a Master’s or Ph.D. in Computer Science, Computer Engineering, or a related field with an accredited school in the US.
The selected candidate will have the opportunity to contribute to a Machine Learning Operations (MLOps) platform, which supports state-of-the-art training and inference features with a focus on sustainable MLOps practices.
The selected candidate will have the opportunity to contribute to a GenAI and AI/ML systems. The selected candidates will work on:
- Advanced AI/ML systems with a focus on next-generation model training, high-performance inference, and intelligent workload orchestration across heterogeneous compute environments.
- Building and optimizing LLM-based systems, designing distributed inference workflows across cloud, edge, RAN, or vehicular platforms.
- Exploring how workload characteristics, model behavior, and system conditions influence latency, throughput, and efficiency.
- Contribute to experimental prototypes, performance analysis, and cross-cluster or multi-tier execution frameworks that support emerging AI applications.
- Reliability, observability, and interpretability aspects of AI-enabled network operations, including system modeling and inference-time interventions for multimodal transformers.
- Collaborate with experienced researchers to investigate real-world constraints such as resource heterogeneity, network dynamics, mobility, and performance variability—helping shape platforms that deliver robust, responsive, and efficient AI services.
We are looking for students with the following background and skillset.
- Advanced AI/ML systems with a focus on next-generation model training.
- Building and optimizing LLM-based systems.
- Strong programming ability in Python; experience with C++, Go, or Java is a plus.
- Solid fundamentals in computer systems, networking, and Linux/Unix environments.
- Experience with PyTorch and modern ML tooling; familiarity with HuggingFace ecosystem.
- Understanding of deep learning, specifically Transformer architectures.
- Exposure to distributed systems, containers, and orchestration tools (Docker, Kubernetes).
- Ability to design experiments, analyze performance, and debug complex system interactions.
- Experience with vLLM, SGLang, TGI, TensorRT-LLM, llama.cpp, DeepSpeed, or Ray
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.
- 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
Top Skills
What We Do
At Nokia, we create technology that helps the world act together. As a trusted partner for critical networks, we are committed to innovation and technology leadership across mobile, fixed and cloud networks. We create value with intellectual property and long-term research, led by the award-winning Nokia Bell Labs. Adhering to the highest standards of integrity and security, we help build the capabilities needed for a more productive, sustainable and inclusive world.
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