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:
- 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.
- Contributing to hands-on project delivery.
- Developing deep knowledge of customer problems, workflows, and data; identifying relevant state-of-the-art technologies to create customer value.
- Translating complex business problems into well-defined projects with clear scope and objectives, ensuring timely and effective delivery.
- Providing insights and strategic input to business and Labs leadership on AI strategies.
- Sharing information, valuing diverse ideas, and collaborating effectively within a cross-functional team.
- Building strong relationships with internal stakeholders and providing AI expertise.
- Mentoring and coaching scientists and engineers, fostering a culture of continuous learning and innovation.
- Maintaining expertise in relevant areas evidenced through deliverables, publications, and intellectual property creation.
- 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:
- A PhD in a relevant discipline or a master's degree with substantial experience.
- Extensive hands-on experience building NLP/IR systems for commercial applications.
- Proven ability to mentor, coach, and manage teams.
- Strong software engineering skills for prototyping and delivery.
- Experience translating research into practical applications addressing customer needs.
- Leadership experience in scoping, prioritizing, and guiding technical work.
- Experience working with Product, Engineering, and stakeholders in agile environments.
Technical Qualifications:
- Strong understanding of classical ML techniques for NLP.
- Knowledge of deep learning approaches for NLP, including transformer models.
- Understanding of large model architectures.
- Experience with text-heavy NLP projects.
- Hands-on experience with generative AI technologies and frameworks like RAG, pre-training/fine-tuning, prompt engineering, and agentic frameworks.
- Proficiency in Python, Git, AWS, and Azure for model development and deployment.
- Experience with UI development, rapid prototyping, and agile practices.
Additional Qualifications:
- Experience with search and question answering systems, especially from large corpora or long documents.
- Experience developing applications in the legal domain, such as document review or drafting.
- Publications in relevant academic venues like ACL, EMNLP, NeurIPS, etc.