AI/ML Intern

AI/ML Intern United States (On-site) 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. Your responsibilities 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. Your skills and experience 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 More information Some of our benefits for students in the US: 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 Disclaimer for US/Canada Nokia maintains broad annual base salary ranges for its roles in order to account for variations in knowledge, skills, experience and market conditions, and with consideration to internal peer equity. Check the salary ranges in the job info section for this role. All North America job posts will post for a minimum of 3 calendar days and up to 180 days or until candidate/s identified. About Us Advancing connectivity to secure a brighter world. 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. Learn more about life at Nokia. About the Business Group The Strategy and Technology organization drives Nokia’s future innovation by identifying value-creation opportunities, setting a unified company vision, and developing coherent business, technology, and architecture strategies. It establishes a research foundation for new products and solutions while providing critical infrastructure to support secure and effective execution across all Nokia business units. Nokia Bell Labs, the world-renowned industrial research arm of Nokia has pioneered breakthrough foundational technologies over the past 100 years like the transistor, laser, Unix, and solar cell - shaping modern communications, computing and connectivity. Today, it drives innovation in AI, quantum computing, 6G, and space communications, bridging groundbreaking research to real-world applications with meaningful impact on society. With ten Nobel Prizes and five Turing Awards, Nokia Bell Labs continues to define the future of technology. 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. Job Info Job Category Corporate Services Posting Date 12/11/2025 Degree Level Bachelor’s degree Job Schedule Full time Job Type Fixed Term Student Intern (under 3 months ONLY) Job Identification 27580 Role Type Individual contributor US/Canada Salary Range $20.10 -$70.40 USD per hour. Locations 600-700 Mountain Avenue, Murray Hill, New Jersey, 07974-0636, US (On-site)