About the role
Valo
Founding Data Scientist
(LLM Post-Training & Reinforcement Learning)
in partnership with
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Overview
Valo is building an AI-powered personal assistant for every Indian — one that doesn't just answer
questions but gets real-world tasks done.
From making calls and managing bookings to coordinating services and payments, Valo is building
autonomous AI agents that plan, execute, and deliver verified outcomes.
We are a seed-funded startup founded by experienced leaders from Zomato, IDFC FIRST Bank,
Kapture CX, Microsoft, and Grab, building proprietary AI models and infrastructure for millions of
users.
We're looking for a Founding Data Scientist to build and post-train language models that power
autonomous AI agents.
You'll own the complete model improvement lifecycle, from training data and reward design to SFT,
reinforcement learning, evaluation, and production deployment.
This is a deeply hands-on role working directly with the founders to build proprietary AI models that
learn from real-world outcomes.
Key Responsibilities
LLM Post-Training: Fine-tune open-weight models (Llama, Qwen, Gemma) using SFT, DPO, and
RL techniques.
Reinforcement Learning: Design reward functions and optimize model policies using real-world
task outcomes and user preferences.
Agent Data Pipelines: Build high-quality training datasets from agent trajectories, tool interactions,
and preference signals.
Model Evaluation: Develop benchmarks to measure reasoning, tool use, decision-making, and task
completion.
Training & Inference: Run distributed training and high-throughput inference using PyTorch, FSDP,
DeepSpeed, vLLM, and SGLang.
Production Ownership: Deploy, optimize, and continuously improve fine-tuned models.
Requirements:
Hands-on experience post-training open-weight LLMs using SFT, DPO, and/or RL techniques, with
production deployment experience.
Strong expertise in Python, PyTorch, transformers, attention mechanisms, and LLM
architectures.
Experience with LoRA/PEFT, distributed training (FSDP/DeepSpeed), mixed precision, and multiGPU infrastructure.
Practical experience with vLLM/SGLang for high-throughput inference and agent rollouts.
Experience building LLM training datasets, agent trajectories, preference datasets, and
evaluation frameworks.
Strong understanding of model optimization, experimentation, and failure analysis.
Good to Have: Experience with PPO, GRPO, RLHF, reward modeling, and long-horizon
autonomous agents.
Ideal Candidate
Engineers and scientists who have actually trained, fine-tuned, and shipped LLMs, not just built
applications using LLM APIs.
You should enjoy solving complex ML problems, experimenting with model architectures and
training techniques, and taking end-to-end ownership in a fast-moving founding team.
Why Join Valo?
Build proprietary AI models from the ground up.
Work on challenging problems in LLM post-training, reinforcement learning, and agentic AI.
Collaborate directly with experienced AI and product founders.
Shape the technical foundation of an AI assistant designed for millions of Indians.
Location: Gurgaon
Experience: 8+ Years
Work Mode: 6 days a week
Apply Here
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