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Job Description
About the Company:
We are working with a pioneering financial services organization operating at the intersection of law and AI innovation. This company is redefining how AI technologies support legal and financial professionals—driving efficiency, insight, and scale in a highly regulated industry. As they expand, they’re investing heavily in cutting-edge NLP and LLM research to power their next generation of AI products. This is a rare opportunity to contribute to AI innovation with tangible, real-world impact.
THE ROLE: Director of AI Research
As a Director of AI Research, you will be central to developing and deploying advanced natural language processing solutions that tackle complex challenges in the legal-financial domain. Reporting into senior technical leadership, your work will span early-stage research through production-grade implementation.
Key Responsibilities:
• AI Model Innovation: Design and implement novel NLP and LLM architectures tailored for domain-specific applications across legal and financial datasets.
• Research to Production: Own projects from prototyping through production, leading 0-to-1 development of scalable NLP systems.
• Model Optimization: Enhance model performance through fine-tuning, prompt engineering, retrieval augmentation, and inference optimization.
• Cross-Functional Collaboration: Work closely with product, engineering, and executive teams to align AI capabilities with strategic goals.
• Thought Leadership: Help shape internal best practices in applied NLP/LLM development, and contribute to research papers and IP generation.
• Mentorship & Guidance: Provide technical insight and mentorship to junior researchers and engineers.
YOUR SKILLS AND EXPERIENCE:
We’re seeking an experienced, hands-on NLP practitioner with a deep understanding of AI system development:
• 5–8 years of professional experience in applied NLP or LLM-based system development.
• Strong foundation in building and deploying NLP models in production settings.
• Proficiency with Python and modern ML/NLP frameworks (e.g., PyTorch, TensorFlow, HuggingFace, spaCy, etc.).
• Demonstrated experience scaling models across large, unstructured datasets.
• Applied research background with a proven track record of translating research into real-world tools and platforms.
• Deep understanding of LLM architectures, fine-tuning, prompt engineering, and retrieval-augmented generation (RAG).
• Excellent communication skills and comfort working in agile, high-ownership environments.
• PhD or Master’s degree in Computer Science, AI, Computational Linguistics, or related field (PhD preferred).
• Publication record in respected AI/NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICLR) is highly desirable.