Applied AI Scientist : AVP - AI Lab (Research)

Join us as a “AI Lab (Research) – Applied AI Scientist ” at Barclays. The role owner will be responsible for ideation, maintenance, development and operations of machine learning and artificial intelligence systems in Barclays, specifically in the AI Lab for Research. The focus of the role will be in shaping the future of our award-winning franchise for quantitative and fundamental finance in the eyes of AI. We are embracing the change, and agentic research is a concept that we are implementing every day. As an Applied AI Scientist, we will expect that you come with a modern technology stack that allows us to deliver fast and at scale. Specifically, we are looking for people that thrive for challenges and want to take all the foundational AI Models and repurpose them to finance.

To be successful as an Applied AI Scientist, we would expect that you have:

Required Qualifications:

• Proven track record of working in AI, specifically in domains such as research, scientific publications and finance
• 5+ years of experience with Python as a programming and scripting language
• 3+ years of experience with Machine Learning, Artificial Intelligence and Generative AI
• Working knowledge and strong understanding of transformers, reasoning-focused model architectures, and inference-time compute strategies such as ReAct, chain-of-thought, tree-of-thought, self-consistency, Monte Carlo Tree Search (MCTS) for reasoning
• Hands on experience with LLM fine-tuning, including reinforcement learning-based methods and preference alignment techniques (such as DPO, PPO, GRPO) and parameter-efficient fine-tuning methods (LoRA, QLoRA, adapters)
• Proven experience building and deploying agentic AI harnesses with multi-step reasoning, intent/model routing, tool-use, function calling, memory, etc.
• Proven experience taking use cases from ideation to production in the AI space at scale (Enterprise AIOps experience)
• Excellent stakeholder management and communication skills, as the person will shape the future interacting with the business and technology

Desirable skillsets that would make you awesome:

• Model Training: Experience with PyTorch and Compilers, as we aspire to build new inhouse models, including distributed training, and familiarity with HuggingFace transformers, TRL and PEFT libraries

·         Advanced Training Paradigms: Experience designing and evaluating reinforcement learning-based fine-tuning pipelines for language models, including reward modelling, policy optimisation, and offline/online evaluation in complex domains such as finance

• Agentic AI and Orchestration: Experience with MCP, A2A and tool-use protocols, and orchestration frameworks such as LangGraph, CrewAI, ADK, or similar
• Inference optimization: Knowledge of quantization frameworks (such as TurboQuant), serving frameworks (vLLM, SGLang, Triton), and latency/cost tradeoffs

·         Knowledge Graphs: Experience designing and integrating knowledge graphs (Neo4j, TigerGraph, memGraph), GraphRAG, entity resolution, relationship extraction, and semantic retrieval to ground AI systems in enterprise context

·         Vision Language Models: Experience working with and fine-tuning multimodal AI models, including image-document understanding, entity extraction, visual question answering, OCR-enhanced retrieval

• Experience in AWS and Bedrock (Generative AI), for agentic systems architecture
• Experience managing multiple projects at the same time, PMP

Additional Skills that would be ideal:

• Ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise Wide Risk Management Framework and internal Barclays Policies and Policy Standards.
• Independent, reliable, motivated.
• Willing to learn and share knowledge.
• Experience with database systems, both relational and non-relational.
• Experience in the full development lifecycle, including design, implementation, testing, deployment, and support.
• Experience with version control systems like Git is desirable.
• Basic knowledge of Docker and Kubernetes.
• Experience with continuous integration systems like Jenkins or TeamCity.