Machine Learning Engineer, Chakra

IndiaHybrid

Responsibilities

Architect and develop Chakra end to end: the agent design, conversation management, real-time response evaluation, scoring methodology, and report generation.
Build the systems that ensure interview consistency at scale. Not just model capability, but the infrastructure that makes the 200,000th interview as coherent as the first.
Design evaluation and benchmarking pipelines that measure interview quality, candidate
Build fine-tuning and RLHF workflows to push model judgment past what off-the-shelf models deliver for this specific task.
Own the quality bar. Define what a good interview looks like, instrument how well the system meets that bar, and close the gap systematically.

Software has entered an era where humans and AI build side by side.
The developer's job is shifting from writing code to directing AI agents, and hiring needs to catch up.
Chakra is our bet on what the next generation of that looks like: an AI interviewer built for a world where the interview itself has to be as intelligent as the candidates it is evaluating. Open Problem
Chakra is an AI interviewer.
You have built and shipped agentic or conversational AI systems in production, not just prototypes.
You have a strong intuition for where LLM behavior breaks down under real-world conditions and how to address it systematically.
Experience building multi-turn conversational agents or interview-style AI systems.
Worked with RLHF, Constitutional AI, or preference-based fine-tuning methods.
Background in dialogue systems, conversational evaluation, or rubric-based scoring.
Publications or contributions in agentic AI, LLM reliability, or evaluation of generative systems. You will thrive in this role if

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