Machine Learning Engineer - AI

About the role

Egnyte is a secure multi-cloud platform for content security and governance, serving over 23,000 organizations worldwide. As a Machine Learning Engineer - AI, you will fine-tune and train small language models (SLMs) using Hugging Face, TRL, and adapter methods, optimize them for inference, and deploy to edge, mobile, and local servers. You will also build end-to-end MLOps pipelines and monitor model performance in production. This full-time role is based in India.

What you’ll do

• Fine-tune and train SLMs using Hugging Face, TRL, and adapter methods (LoRA, QLoRA, PEFT)
• Optimize models for inference via quantization, pruning, and knowledge distillation
• Deploy models to edge devices, mobile, and local servers with strict latency targets
• Build end-to-end MLOps pipelines from data ingestion to deployment
• Monitor model accuracy, latency, and hardware utilization in production
• Evaluate model quality using benchmarking frameworks and custom evaluation suites

What you’ll bring

• Train and fine-tune SLMs using Hugging Face and knowledge of adapters
• Apply quantization, pruning, knowledge distillation, and optimization for lightweight, efficient models
• Deploy models to edge devices, mobile, and local servers
• Build end-to-end MLOps pipelines from data ingestion to deployment
• Track model accuracy, latency, and CPU/GPU usage in production
• Evaluate model quality using benchmarking frameworks and custom evaluation suites

Nice to have

• Deployment experience on edge or mobile environments
• Knowledge of ONNX export and cross-platform inference
• MLOps tooling — experiment tracking, model registries, CI/CD for ML

Skills