Senior Research Scientist - Applied AI Team
Our client, a leading hedge fund, is looking for a Senior Applied AI Researcher to join their Applied AI team in London. You will be transforming how professionals interact with artificial intelligence in high-performance environments. This team has developed a suite of AI-powered tools, including custom assistants with deep research capabilities, and is focused on building reasoning models and collaborative AI workspace. We are seeking a Senior Research Scientist to contribute to the development of next-generation AI tools that support decision-making and research workflows. You'll work on impactful projects that bring advanced machine learning research into production, directly influencing how users leverage AI in complex domains. This role offers a unique opportunity to push the boundaries of human + AI collaboration. You'll work within a rich ecosystem of data, models, compute resources, and expert users, enabling rigorous experimentation and innovation.
Responsibilities
- Conduct original research in machine learning, particularly in reinforcement learning, agent architectures, and large language models (LLMs)
- Prototype and develop new ML models and algorithms for real-world deployment
- Collaborate with engineering teams to integrate research into production systems
- Design experiments and analyze results to evaluate model performance
- Engage with end-users to align research with practical applications
- Contribute to the research community through publications, presentations, and open-source projects
- Mentor junior researchers and help shape technical strategy
- Participate in the full research lifecycle from ideation to deployment
Requirements:
- PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field
- Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP)
- 2-5 years of post-PhD experience
- Deep expertise in machine learning, with a focus on NLP and reinforcement learning
- Experience developing ML models in Python (PyTorch)
- Proven ability to translate research into scalable, practical solutions
- Experience deploying ML models in production environments
- Familiarity with financial markets or complex decision-making domains
- Knowledge of vector databases, semantic search, or information retrieval systems
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