Focus area: LLM Training & Evaluation

Location: India, Chennai or Bengaluru preferred · Hybrid

Experience: 6–10 years overall, including hands-on LLM fine-tuning

Role Summary

Own the training, fine-tuning and deployment of specialised language models for our agentic AI platform for airline operations. This is an applied, hands-on role: adapting and serving open-weight models in production.

Key Responsibilities
Build and maintain training-data preparation and model-training pipelines.
Fine-tune and adapt models using supervised fine-tuning, LoRA/QLoRA and other suitable techniques.
Design model-level benchmarks and offline evaluations for the models you train; analyse failures and improve performance.
Manage experiments, dataset and model versions, reproducibility and model documentation.
Deploy and optimise models for quality, latency, throughput and cost.




Work with Agent Engineering on model integration and with the Test & AI Evals Lead on production readiness.

Required Skills & Experience
Solid Python and PyTorch; practical experience with Hugging Face Transformers, Datasets and

PEFT (or equivalent).
Proven hands-on model training or fine-tuning experience, beyond prompting or consuming LLM

APIs.
Experience with dataset preparation, evaluation design, leakage prevention and experiment tracking.
Sound understanding of LLM architectures, embeddings, RAG and model-adaptation trade-offs.
Experience with GPU workloads, model serving, APIs, Docker and cloud infrastructure.
Robust software engineering, troubleshooting and technical communication skills.

Positive to Have
Distributed training, preference optimisation, vLLM/Triton, MLOps, enterprise data privacy.

📌 Senior Ai & Ml Engineer Chennai
🏢 dCortex
📍 Chennai