Research Scientist, Applied AI in भारत

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Research Scientist, Applied AI based in India. Join a fast-moving AI team building the core intelligence behind a revenue-focused AI agent. You will lead applied research across agent architecture, evaluation frameworks, model fine-tuning, and reinforcement learning. Your work will help AI systems make better decisions, use tools effectively, and solve complex, multi-step business problems. You will turn ambitious research hypotheses into measurable improvements and production-ready capabilities. Working closely with AI leadership and product teams, you will shape the evolution of an AI-first platform. This remote opportunity offers substantial technical ownership, meaningful research challenges, and the chance to influence a product at a pivotal stage of growth. Accountabilities - Own and advance the agent harness, including its core execution loop, tools, operating environment, guardrails, and model behavior. - Improve tool selection, context construction, coordination across sub-agents, and the handling of complex, long-running tasks through systematic experimentation. - Evaluate and select models for different tasks, balancing output quality, latency, and computational cost. - Design and implement evaluation frameworks for complex revenue-related tasks, including deal health, risk assessment, and pipeline analysis. - Develop evaluation datasets, benchmarks, grading methodologies, regression detection systems, and automated evaluation pipelines, particularly for tasks without clear ground truth. - Build predictive and scoring models using data from call transcripts, emails, and other business signals to identify cross-deal patterns and generate explainable risk indicators.

- Lead model fine-tuning initiatives and advance the platform toward deeper model training and reinforcement learning. - Research and implement reinforcement learning approaches to improve agent performance and decision-making. - Strengthen context engineering and data quality through entity resolution, information extraction, and the development of knowledge and context graphs. - Take ownership of ambiguous research challenges from initial hypothesis and experimental design through training infrastructure, evaluation, and production deployment. - Collaborate closely with US-based AI leadership and the applied AI team in India to align research priorities with product goals. Requirements - At least 5 years of experience in applied AI research, applied science, or a closely related field, with the technical depth expected of a senior-level individual contributor. - A master’s degree or PhD in Computer Science, Mathematics, Statistics, or another quantitative discipline. - Hands-on experience building and improving agentic systems and agent harnesses, including tool use, multi-step reasoning, and context management. - Practical experience with large language models (LLMs) or large-scale deep learning systems, including model training, fine-tuning, and reinforcement learning from human feedback (RLHF). - A strong understanding of model behavior and the underlying principles that influence how models learn, reason, and respond. - Experience designing evaluation datasets and frameworks, particularly for complex tasks where reliable ground-truth labels are unavailable. - Demonstrated ability to independently define research directions, develop hypotheses, design rigorous experiments, and deliver results with minimal guidance. - Strong analytical, problem-solving, and experimental skills, with the ability to translate research findings into practical production improvements. - Excellent communication and collaboration skills, including the ability to work effectively with a US-based leadership team across time zones.