Applied Scientist

What You'll Do Experiment and Develop • Lead the full model development lifecycle, from research and prototyping to production deployment. • Apply best practices for reproducibility, model governance, and high-quality software delivery. Collaborate • Work closely with product, engineering, and research teams across multiple regions. • Mentor teammates, share knowledge, and contribute to a culture of technical excellence. Deliver • Translate complex business needs into scoped, actionable ML and NLP projects. • Ensure timely, well-managed delivery in a dynamic, fast-paced environment. Innovate • Explore new methods, frameworks, and model architectures. • Drive experimentation with emerging NLP, IR, and LLM techniques. Inspire • Communicate findings clearly to both technical and non-technical audiences. • Help guide enterprise adoption of modern AI technologies. Basic Qualifications • Master's degree in a relevant field or equivalent applied experience. • 3+ years building NLP, IR, or ML systems from inception through production. • Strong software engineering skills for prototyping and iterative development. • Demonstrated experience transforming research concepts into functional prototypes with clear objectives. • Ability to collaborate effectively within diverse, cross-functional teams. • Hands-on exploration of novel NLP or IR models to address real-world challenges. • Experience thriving in fast-paced, agile environments. • Excellent communication skills and strong data-driven decision making. Technical Requirements • Solid understanding of classical ML methods for NLP tasks. • Strong knowledge of deep learning approaches, including transformer-based architectures. • Familiarity with the internals and behavior of large language models. • Experience working on text-heavy NLP projects. • Practical experience with Generative AI techniques such as: • prompt engineering • in-context learning • chain-of-thought prompting • prompt optimization and evaluation • controlled generation • function calling • Experience with RAG architectures, model fine-tuning, and creating training datasets. • Exposure to agentic frameworks (LangGraph, AutoGen, Semantic Kernel, etc.). • Proficiency in Python, Git, and cloud environments (AWS or Azure) for model development and deployment. • Experience with rapid prototyping, lightweight UIs, and agile iteration. Preferred Qualifications • 5+ years designing NLP, IR, or ML systems in industry or research settings. • Background in building search or Q&A systems across large document corpora. • Experience with long-document summarization or high-volume text processing. • Familiarity with legal-tech or document-heavy enterprise workflows. • Publications at major conferences such as ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, ICML, or similar.