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Lead Research Scientist
As a hands-on Applied Scientist and NLP/ML Tech Lead with over a decade of experience, I specialise in building and leading projects at the intersection of language, multimodal understanding, and generative AI. My recent work focuses on developing agentic AI systems and co-pilot experiences that help users create and interact with complex products more intuitively. At Synthesia, I established and led the NLP research team, focusing on enhancing the emotional expressiveness of digital humans. I collaborated closely with the audio and video teams to design experiments, collect and annotate multimodal emotion data, and evaluate models that make avatars more natural and engaging. My team delivered large-scale annotated datasets, developed complex evaluation frameworks, built prototypes from concept to production, and drove product innovation through close collaboration with engineering and product functions. Previously at Meta, I contributed to applied AI research for integrity and customer support, leveraging few-shot learning and extreme classification to build scalable, high-impact solutions. I am passionate about translating research advances into deployable, user-centric products—combining product thinking, technical leadership, and a strong delivery mindset. Known for my ability to communicate effectively across disciplines, I thrive in cross-functional environments that value experimentation, learning, and building trustworthy AI systems that make technology more human. **Areas of Expertise** LLMs & Multimodal AI • Agentic Workflows • Emotion Modelling • Product Discovery & Delivery • Cross-Functional Leadership • NLP Research • Applied Machine Learning
University College London
MRes/PhD, Natural Language Processing and Machine Learning
January 1, 2011 – January 1, 2016
King's College London
MSc Engineering with Finance
January 1, 2009 – January 1, 2011
Epic Games
Lead Research Scientist
April 1, 2026 – Present
London Area, United Kingdom · Hybrid
Synthesia
Research Engineering Manager
January 1, 2025 – Present
Hybrid
Synthesia
NLP Research Lead
February 1, 2023 – January 1, 2025
Hybrid
Research Scientist
August 1, 2018 – January 1, 2023
London Area, United Kingdom
Bloomsbury AI
Research Scientist
January 1, 2018 – August 1, 2018
Techhub London
Gluru
R&D NLP and Machine Learning Engineer
January 1, 2017 – December 1, 2017
London Area, United Kingdom
SunGard
Software Developer
July 1, 2008 – September 1, 2011
Factset Research Systems
Software Engineer
December 1, 2006 – June 1, 2008
Cultural Fit Analysis
The candidate's career trajectory shows a strong focus on cutting-edge AI research and development, particularly in NLP and ML, across various high-profile tech companies (Facebook, Synthesia, Epic Games). Their academic background (PhD in NLP/ML) further reinforces this specialization. The diversity of projects, from AI integrity and customer support to AI-assisted video creation and conversational AI, indicates adaptability and a broad interest within the ML domain. The progression into leadership roles suggests a proactive and growth-oriented mindset. The early career in software development (Java, Spring MVC) provides a foundational understanding of software engineering, which is beneficial for an ML Engineer role, though the primary focus has shifted significantly towards research and ML. The candidate's profile aligns well with a culture that values innovation, research, and practical application of advanced AI.
Soft Skills & Operational Fit
The candidate's experience as a Research Engineering Manager and NLP Research Lead at Synthesia, along with their role as Lead Research Scientist at Epic Games, indicates strong leadership, team direction, and cross-organizational delivery skills. Their work at Facebook on AI Integrity and AI for Customer Support suggests an ability to tackle complex, policy-aware problems and improve user experiences, which implies strong problem-solving and strategic thinking. The descriptions highlight hands-on involvement in experimentation, evaluation, and integration, demonstrating a blend of technical depth and operational execution.