Research Scientist, Applied AI

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.
• Publications in leading peer-reviewed conferences or journals are preferred.
• Must-have skills: Agentic systems, agent harness design, and model fine-tuning.
• Good-to-have skills: LLMs, applied AI, and AI research.

Benefits

• Competitive compensation: Annual salary range of INR 90–100 lakh (₹90,00,000–₹1,00,00,000).
• Equity opportunity: Access to equity in an early-stage company ahead of its next funding round.
• Remote flexibility: Work remotely from India, with opportunities for the team to meet in person in Bangalore.
• Meaningful technical ow…