At a Glance
- Tasks: Lead AI research and development, shaping the future of technology at Lenovo.
- Company: Join Lenovo's global AI Technology Center, a leader in innovation.
- Benefits: Career growth, flexible hybrid work, performance rewards, and training opportunities.
- Why this job: Make a real impact in AI with cutting-edge projects that touch lives worldwide.
- Qualifications: PhD in relevant field and extensive experience in ML research required.
- Other info: Collaborative environment with mentorship opportunities and industry-leading resources.
The predicted salary is between 48000 - 72000 £ per year.
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.
- Drive research-to-production pipeline: Ensure research outputs meet production quality standards. Partner with Agentic Engineers on model integration, latency optimization, and deployment.
- External research engagement: Author internal whitepapers and (where appropriate) external publications. Represent Lenovo at conferences, workshops, and industry events.
- Mentor and grow researchers: Guide junior researchers on problem formulation, experiment design, and paper writing. Create an environment of technical excellence and continuous learning.
- Cross-functional leadership: Coordinate with Infrastructure team on GPU clusters and MLOps. Work with Data team on data requirements. Support BU teams in translating research to product features.
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.
Staff AI Engineer, LLM Researcher in Farnborough employer: Lenovo
Contact Detail:
Lenovo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff AI Engineer, LLM Researcher in Farnborough
✨Tip Number 1
Network like a pro! Attend AI conferences, workshops, and meetups to connect with industry leaders and fellow researchers. Don't be shy—introduce yourself and share your passion for AI; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, research papers, and any relevant work. This is your chance to demonstrate your expertise in deep learning and NLP, so make it visually appealing and easy to navigate.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as you'll likely need to communicate your ideas clearly to non-technical stakeholders.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight how your experience aligns with our mission at Lenovo, and don’t forget to follow up after submitting!
We think you need these skills to ace Staff AI Engineer, LLM Researcher in Farnborough
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Staff AI Engineer role. Highlight your experience with deep learning, reinforcement learning, and any relevant projects that align with our mission at Lenovo. We want to see how your skills fit into our vision!
Showcase Your Research: Don’t forget to include your publications and any significant research contributions. If you've authored papers in top-tier venues, let us know! This is your chance to shine and show us how you can contribute to our cutting-edge AI initiatives.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon where possible. We appreciate a well-structured application that makes it easy for us to see your qualifications and passion for the role.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way to ensure your application gets to the right people. Plus, you’ll find all the details about the role and our team there!
How to prepare for a job interview at Lenovo
✨Know Your AI Stuff
Make sure you brush up on your deep learning fundamentals, especially around PyTorch and transformer architectures. Be ready to discuss your hands-on experience with HuggingFace Transformers and parameter-efficient fine-tuning methods like LoRA. They’ll want to see that you can not only talk the talk but also walk the walk!
✨Research the Company
Dive into Lenovo's AI initiatives and their vision for the future. Understanding their products and how AI fits into their strategy will help you align your answers with their goals. Plus, it shows genuine interest, which is always a plus in interviews!
✨Prepare for Technical Questions
Expect to face some technical challenges during the interview. Brush up on classification metrics and experiment design principles, and be prepared to discuss your previous research and how it translates to production systems. Practising coding problems related to Python and data processing can also give you an edge.
✨Show Your Mentorship Skills
Since mentoring junior researchers is part of the role, think of examples where you've guided others or led a team. Highlight your ability to create a collaborative environment and share your experiences in problem formulation and experiment design. This will demonstrate your leadership potential!