Senior AI & ML Engineer

dCortex; Chennai; Hybrid; INR 400,000 - 700,000; Full time

Job summary

dCortex is seeking an experienced ML Engineer to own the training, fine-tuning and deployment of specialised language models for our airline-operations platform. This is a hands-on role focused on adapting and serving open-weight models in production, with emphasis on practical delivery and measurable improvements.

You will design training pipelines, run supervised fine-tuning (LoRA/QLoRA), evaluate models and monitor latency, throughput and cost.

Qualifications

• Hands-on experience training or fine-tuning LLMs beyond prompting.
• Experience with dataset preparation and evaluation design.
• Knowledge of LLM architectures, embeddings, RAG and model-adaptation trade-offs.
• Experience with GPU workloads, model serving, APIs, Docker and cloud infrastructure.
• Strong Python and PyTorch skills; familiarity with Hugging Face Transformers.
• Excellent software engineering and technical communication.

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.

Skills

Python

PyTorch

Hugging Face Transformers

Datasets

PEFT

LLM Fine-tuning

Dataset prep

Evaluation design

Experiment tracking

LLM architectures

Embeddings

RAG

Model adaptation

GPU workloads

Model serving

APIs

Docker

Cloud

Software engineering

Troubleshooting

Technical communication

Tools

Docker

Job description

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
• 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

• Strong 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.
• Strong software engineering, troubleshooting and technical communication skills.

Good to Have

• Distributed training, preference optimisation, vLLM/Triton, MLOps, enterprise data privacy.