LLM Engineer

About the Role

Were looking for an experienced and motivated LLM Engineer to lead the fine-tuning and optimization of large language models on billion-scale datasets. In this high-impact role, you’ll build scalable ML infrastructure, adapt open-source models to domain-specific data, and shape intelligent systems that operate at real-world scale.

You’ll work with advanced open-source models (such as LLaMA, Mistral, or Falcon), implement parameter-efficient fine-tuning strategies, and build robust pipelines that transform raw behavioral and textual signals into aligned, production-ready models.

This is an ideal role for someone who enjoys solving deep learning challenges, scaling models across massive datasets, and laying the foundation for future, intelligent AI systems.

What You’ll Do

Fine-tune and adapt open-source LLMs (e.g., LLaMA, Mistral, Falcon) on massive domain-specific datasets

Build scalable pipelines for data preprocessing and model fine-tuning using big data processing frameworks

Apply fine-tuning strategies such as LoRA, PEFT, and RLHF to align models efficiently

Optimize performance using distributed training techniques for multi-GPU or multi-node environments

Design and manage experiments, run training cycles, and evaluate model performance across key quality metrics

Monitor model behavior over time and iterate on tuning approaches for robustness and alignment

Collaborate across engineering, infrastructure, and product teams to integrate models into user-facing applications

What We’re Looking For

You're someone who thrives on scaling deep learning systems, solving real-world modeling challenges, and improving models through experimentation and iteration.

3–5 years of experience fine-tuning LLMs or large-scale NLP models

Deep understanding of Machine Learning, Deep Learning, NLP,and LLMs,

Strong proficiency in Python (required);

Hands-on experience with PyTorch and Hugging Face Models

Familiar with distributed training strategies for large models (e.g., DeepSpeed, FSDP, etc)

Experience handling and processing large datasets using big data frameworks

Comfortable running experiments, evaluating results, and refining models through iterative tuning

Experience working with or contributing to open-source LLMs

Role & responsibilities

Preferred candidate profile