Applied Scientist Manager

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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.