Staff Applied Scientist in भारत

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Staff Applied Scientist based in India. We are seeking an experienced Staff Applied Scientist to shape the knowledge and AI foundations powering next-generation software products. In this remote role, you will design production-ready knowledge graphs, intelligent AI agents, and advanced retrieval systems that transform unstructured information into reliable, actionable insights. You will combine deep expertise in machine learning, natural language processing, and large language models (LLMs) with strong engineering capabilities to deliver measurable customer value. Beyond hands-on development, you will define technical strategy, establish evaluation standards, and guide critical decisions on AI architecture and implementation. You will collaborate with multidisciplinary teams across India, the UK, and North America in a globally distributed, remote-first environment. This is an opportunity to drive applied AI innovation, mentor experienced technical professionals, and influence how intelligent, knowledge-driven solutions are built and scaled. Accountabilities: - Knowledge Graph Development: Design, build, and maintain production-grade knowledge graphs that transform unstructured content into structured, reliable, and accessible knowledge. Lead ontology design, information extraction, and entity resolution to improve data quality and usability. - AI Agents and Intelligent Retrieval: Develop and deploy LLM-powered agents and agentic retrieval systems capable of finding, validating, and using relevant information. Implement planning, tool integration, and orchestration mechanisms to deliver dependable, context-aware results. - Model Evaluation and Continuous Improvement: Establish robust evaluation frameworks and quality metrics to measure model performance and determine production readiness. Incorporate real-world user feedback to improve knowledge accuracy, retrieval relevance, and overall system effectiveness.

- Applied Machine Learning and NLP: Apply advanced machine learning, natural language processing, retrieval-augmented generation (RAG), and LLM fine-tuning techniques to solve complex product challenges. Combine modern language models with classical machine learning approaches to improve reliability and performance. - Technical Strategy and Architecture: Set technical direction for applied science initiatives, evaluate emerging technologies, and make informed build-versus-buy decisions. Establish scalable approaches to experimentation, model deployment, and production engineering. - Cross-Functional Product Collaboration: Partner with Product, Engineering, and AI teams to translate research findings into practical product capabilities. Balance technical feasibility, system performance, and customer value when prioritizing solutions. - Technical Leadership and Mentorship: Mentor engineers, data scientists, and senior technical contributors. Establish best practices for experimentation, model evaluation, software quality, and production deployment while fostering a culture of scientific rigor and continuous learning. - Responsible and Reliable AI: Improve agent reliability through systematic testing, guardrails, human review, and ongoing performance monitoring. Ensure AI systems meet established quality standards before their release to customers. Requirements: - Applied Machine Learning Experience: At least 8 years of experience applying machine learning techniques in production environments, with a demonstrated ability to develop and deploy solutions that deliver measurable business or customer outcomes. - NLP, LLMs, and RAG Expertise: Strong knowledge of natural language processing, large language models, and retrieval-augmented generation. Hands-on experience fine-tuning LLMs and applying classical machine learning techniques is required.