Research Scientist, Applied AI

Research Scientist, Applied AI

Salary

₹90 - 100 LPA

Experience

• 5+ yrs

Location

Remote (India)

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Research Scientist, Applied AI

Human Capitalists

Job descriptionApplication

About the role

• About the Role Build the core agent behaviour behind a revenue-focused AI agent, from the agent harness and evals to fine-tuning and reinforcement learning, and take hard research problems from hypothesis to production.

Key Responsibilities

• Own and advance the agent harness: the core loop, tools, environment, guardrails, and model behaviour that power the agent.
• Improve how the agent selects tools, builds context, coordinates across sub-agents, and handles long, multi-step tasks, through systematic experimentation.
• Drive model selection across tasks, balancing answer quality, latency, and cost.
• Design and build evaluations for complex revenue tasks such as deal health, risk, and pipeline questions, including benchmarks, regression detection, and automated eval pipelines.
• Build eval datasets and grading methods for tasks that have no clean ground truth.
• Build scoring and prediction models, such as deal health scores from call transcripts and emails, cross-deal pattern mining, and explainable risk signals.
• Lead fine-tuning work as the platform moves from harness-heavy work into deeper model training.
• Research and design reinforcement learning (RL) 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 the training, eval, and grading infrastructure, and ship results to production.
• Work closely with the US-based Head of AI and the applied AI team in India.

Qualifications

• MS or PhD in Computer Science, Mathematics, Statistics, or another quantitative discipline.

• 5+ years of experience in applied AI research or applied science, at a senior level.

• Hands-on experience building and improving agentic systems and agent harnesses, including tool use, multi-step reasoning, and context management.

• Hands-on experience with LLMs or large-scale deep learning systems, including training, fine-tuning, and RLHF.

• A clear understanding of why models behave the way they do, not only how to use them.

• Experience designing eval datasets or frameworks, especially for tasks without clean ground truth.

• Proven ability to scope and drive ambiguous research with minimal guidance.

• Publications at top-tier peer-reviewed conferences or journals are preferred.

• Comfortable working with a US-based leadership team across time zones.

• Benefits & Perks

• Competitive salary and equity at Series A, ahead of the next funding round.

• A remote role, with the team meeting in person in Bangalore.

• Meaningful scope from day one: you will own core agent capabilities, not just support them.

• Direct work with the Head of AI and a tight feedback loop with founders and product.

• A sharp, low-ego team that moves fast and communicates directly.

• A chance to shape an AI-first product at a pivotal stage, as it moves from harness work into fine-tuning and RL.

• Hiring Process Stage

• 1: Apply and submit the application form

• Stage 2: Introductory round with Co-founder Stage

• 3: Detailed role discussion with Leadership team

• Stage 4: Final Discussion with Co-founders

• Must-have skills

• Agentic SystemsAgent Harness Designmodel finetuning

• Good-to-have skills

• LLMApplied AIAI research

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