Applied Scientist Manager

Our client is looking for a Manager of Applied Research where you will be part of a global cross-functional team of experts. They hire specialists across a variety of AI research areas, as well as Engineering and Design, to drive the company’s digital transformation. This opportunity combines hands-on project work as well as project and people leadership.

As a Manager of Applied Scientist, you will:

• Lead a high performing team of applied researchers throughout the full research and product development life cycle from ideation and PoC through to production scaling and feedback driven iteration.
• Contribute to hands-on delivery on important projects.
• Develop in-depth knowledge of customer problems, workflows and data. Identify state of the art technology relevant to their products and leverage them to create value for their customers.
• Translate complex business problems into projects with clearly defined scope and objectives, and be accountable for timely, well-managed deliverables.
• Provide input and insights to the business and Labs leadership on long-term AI strategy.
• Share information, value diverse ideas, and partner effectively with colleagues in a cross-functional team.
• Build close relationships with internal project stakeholders and provide AI subject matter expertise.
• Mentor and coach scientists and engineers on best practices and fostering a culture of continuous learning, innovation, and collaboration.
• Maintain scientific and technical expertise in one or more relevant areas as demonstrated through product deliverables, published research, and creating intellectual property.
• Be a proactive communicator who is excited to share your work. You will be articulate and compelling in describing ideas to both technical and non-technical audiences. You will help lead the way in the adoption of AI across the enterprise.

About You:

You’re a fit for the role of Manager of Applied Scientist if your background includes:

• PhD in a relevant discipline or master’s plus a comparable level of experience.
• Significant number of years of hands-on experience building NLP / IR systems for commercial applications.
• Demonstrable ability to mentor and coach colleagues as well as proven management experience.
• Solid software engineering skills for prototyping and ensuring well-managed software delivery.
• Demonstrable ability to connect cutting edge research to customer needs and creating well-structured research/project plans into working applications.
• Experience as a technical leader, scoping, prioritizing, coordinating and guiding the work of others.
• Experience collaborating with Product, Engineering and other business stakeholders in an agile manner to demonstrate value and iterate with customer feedback.

Technical Qualifications:

• Solid understanding of classic ML techniques used for NLP problems.
• Solid understanding of DL approaches used for NLP tasks such as transformer-based models.
• Working understanding of inner workings of large language models.
• Experience working on text heavy NLP projects.
• Practical experience using generative AI technologies (prompt engineering, in-context learning, chain-of-thoughts, prompt optimization, auto-evaluation, function calling, controlled generation, etc.).
• Practical experience using RAG frameworks, pre-training/fine-tuning language models, and data curation/generation for training/fine-tuning language models.
• Practical experience using agentic frameworks for building applications (LangGraph, AutoGen, Semantic Kernel, etc.).
• Proficiency in Python, Git, AWS, Azure for remote model development and deployment.
• Experience building lightweight UIs, iterating on greenfield concepts, applying agile development practices and rapid prototyping.

Preferred Qualifications:

• Prior work on search and question answering from large corpora and/or long document summarization.
• Experience building applications for the legal domain, such as document review or document drafting.
• Publications at relevant venues such as ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, ICML, KDD or similar conferences and venues.