Staff AI Engineer, LLM Researcher

This role is based at Imperial College London. Applicants must be located in London, as the position requires on-site work at least three days per week under our 3:2 hybrid policy.

The Lenovo AI Technology Center (LATC)—Lenovo’s global AI Center of Excellence—is driving our transformation into an AI-first organization. We are assembling a world-class team of researchers, engineers, and innovators to position Lenovo and its customers at the forefront of the generational shift toward AI. Lenovo is one of the world’s leading computing companies, delivering products across the entire technology spectrum, spanning wearables, smartphones (Motorola), laptops (ThinkPad, Yoga), PCs, workstations, servers, and services/solutions.

This unmatched breadth gives us a unique canvas for AI innovation, including the ability to rapidly deploy cutting-edge foundation models and to enable flexible, hybrid-cloud, and agentic computing across our full product portfolio. To this end, we are building the next wave of AI core technologies and platforms that leverage and evolve with the fast-moving AI ecosystem, including novel model and agentic orchestration & collaboration across mobile, edge, and cloud resources.

This space is evolving fast and so are we. If you’re ready to shape AI at a truly global scale, with products that touch every corner of life and work, there’s no better time to join us.

Responsibilities

• Define research agenda: Identify high-impact research problems aligned with product needs. Set technical direction for intent understanding and agentic learning capabilities. Translate BU requirements into research roadmaps.
• Architect learning systems: Design end-to-end intent classification and agentic learning architectures. Make key decisions on model selection, training strategies, and evaluation frameworks.
• Lead RLHF & alignment research: Own the design of reinforcement learning pipelines for agent optimization. Define reward modeling approaches, safety constraints, and alignment strategies.

Core Skills

• Strong foundation in deep learning: PyTorch, transformer architectures, attention mechanisms, training dynamics.
• Hands-on experience with HuggingFace Transformers, tokenization, and embedding models.
• Expert level knowledge of parameter-efficient fine-tuning methods (LoRA, adapters) and PEFT libraries.
• Understanding of classification metrics (precision, recall, F1) and experiment design principles.
• Proficiency in Python, with experience in data processing (pandas, numpy) and visualization (matplotlib, seaborn).
• Ability to read and implement techniques from academic papers.

Bonus Skills

• Experience with reinforcement learning (PPO, DPO) or RLHF pipelines (TRL library).
• Familiarity with distributed training (DDP, FSDP, DeepSpeed).
• Background in NLP tasks: NER, semantic similarity, question answering, or dialogue systems.
• Experience with experiment tracking tools (MLFlow, Weights & Biases).
• Exposure to agentic AI concepts (ReAct, chain-of-thought, tool use).
• Industry experience at leading AI labs.

Qualifications

• PhD in Computer Science, Machine Learning, NLP, or related field; MS with exceptional publication record considered.
• 5+ years post-PhD (or 7+ years post-MS) experience in ML research, including industry experience.
• First-author publications at top-tier venues (NeurIPS, ICML, ICLR, ACL, EMNLP) with demonstrated citation impact.
• Track record of research translated to production systems or products.
• Experience mentoring junior researchers or leading small research teams.

What we offer

• Opportunities for career advancement and personal development
• Access to a diverse range of training programs
• Performance-based rewards that celebrate your achievements
• Flexibility with a hybrid work model (3:2) that blends home and office life
• Electric car salary sacrifice scheme
• Life insurance