Document Review jobs in United Kingdom

Job Description

Manager of Applied Science

About the role

Our client is looking for a Manager of Applied Research to join a global cross-functional team of experts. The team includes specialists across various AI research areas, Engineering, and Design, to drive digital transformation. This role involves both hands-on project work and leadership responsibilities.

As a Manager of Applied Scientist, your responsibilities include:

1. Leading a high-performing team of applied researchers throughout the research and product development lifecycle, from ideation and proof of concept to production scaling and iterative feedback.
2. Contributing to hands-on project delivery.
3. Developing deep knowledge of customer problems, workflows, and data; identifying relevant state-of-the-art technologies to create customer value.
4. Translating complex business problems into well-defined projects with clear scope and objectives, ensuring timely and effective delivery.
5. Providing insights and strategic input to business and Labs leadership on AI strategies.
6. Sharing information, valuing diverse ideas, and collaborating effectively within a cross-functional team.
7. Building strong relationships with internal stakeholders and providing AI expertise.
8. Mentoring and coaching scientists and engineers, fostering a culture of continuous learning and innovation.
9. Maintaining expertise in relevant areas evidenced through deliverables, publications, and intellectual property creation.
10. Communicating proactively, articulately sharing work with both technical and non-technical audiences, and leading AI adoption across the enterprise.

About You:

If your background includes:

1. A PhD in a relevant discipline or a master's degree with substantial experience.
2. Extensive hands-on experience building NLP/IR systems for commercial applications.
3. Proven ability to mentor, coach, and manage teams.
4. Strong software engineering skills for prototyping and delivery.
5. Experience translating research into practical applications addressing customer needs.
6. Leadership experience in scoping, prioritizing, and guiding technical work.
7. Experience working with Product, Engineering, and stakeholders in agile environments.

Technical Qualifications:

1. Strong understanding of classical ML techniques for NLP.
2. Knowledge of deep learning approaches for NLP, including transformer models.
3. Understanding of large model architectures.
4. Experience with text-heavy NLP projects.
5. Hands-on experience with generative AI technologies and frameworks like RAG, pre-training/fine-tuning, prompt engineering, and agentic frameworks.
6. Proficiency in Python, Git, AWS, and Azure for model development and deployment.
7. Experience with UI development, rapid prototyping, and agile practices.

Additional Qualifications:

1. Experience with search and question answering systems, especially from large corpora or long documents.
2. Experience developing applications in the legal domain, such as document review or drafting.
3. Publications in relevant academic venues like ACL, EMNLP, NeurIPS, etc.