Research Scientist

• Own and advance the agent harness: the core loop, tools, environment, guardrails, and model behaviour that power the agent
• Improve agent tool selection, context construction, sub-agent coordination, and handling of long, multi-step tasks through systematic experimentation
• Drive model selection across tasks while balancing answer quality, latency, and cost
• Design and build evaluations for complex revenue tasks, including benchmarks, regression detection, and automated evaluation pipelines
• Build evaluation datasets and grading methods for tasks without clean ground truth
• Build scoring and prediction models, including deal health scores, cross-deal pattern mining, and explainable risk signals
• Lead fine-tuning work as the platform moves into deeper model training
• Research and design reinforcement learning approaches that improve agent behaviour
• Improve context engineering and data quality through entity resolution, information extraction, and knowledge and context graphs
• Own ambiguous research problems end-to-end: form hypotheses, design experiments, build training, evaluation, and grading infrastructure, and ship results to production
• Work closely with the US-based Head of AI and applied AI team in India

Explore Research Scientist, Applied AI at Weekday (YC W21). Review requirements and application details.