Senior Machine Learning Engineer

Overview

IDfy is Asia’s leading TrustStack, trusted by the best, with global expertise and enterprise-grade tech, we’re solving trust challenges, making compliance easy, fraud detection smarter, and onboarding seamless. Our clients include HDFC Bank, Zomato, Amazon, PhonePe, Paytm, HUL and many others. With more than 13+ years of experience and 2 million verifications per day, we are pioneers in this industry. IDfy’s three platforms- OnboardIQ, OneRisk, and Privy - come together to form one seamless solution enabling trust.

OnboardIQ

An onboarding platform that accelerates growth with frictionless omni-channel onboarding, while mitigating fraud and improving quality of account.

OneRisk

A fraud and risk management platform to mitigate financial, legal, and reputational risks and avoid losses with proactive fraud prevention. It covers individual risk, entity risk, and asset risk.

Privy

A privacy and data governance platform to ensure DPDPA compliance through trust and privacy governance suite and avoid monetary and reputational loss.

The Role - We’re hiring a Machine Learning Engineer to build and deploy production-grade AI systems across NLP, Computer Vision, and Generative AI. If you enjoy taking models from prototype all the way to scalable, reliable production services, this role is for you.

What You’ll Do

Build, fine-tune, and deploy NLP, CV, and Generative AI models (LLMs, transformers, diffusion models, vision models, etc.)

Develop robust ML pipelines, CI/CD workflows, and scalable inference services

Deploy models on cloud platforms (AWS/GCP/Azure) using Docker & Kubernetes

Monitor models for drift, performance, and reliability

Collaborate with product, data, and engineering teams to deliver real-world AI solutions

What We’re Looking For

3-5 years experience as an ML Engineer or similar role

Strong Python skills + experience with PyTorch/TensorFlow, Hugging Face, OpenCV

Hands-on experience deploying production ML/GenAI systems

Solid understanding of MLOps tools (MLflow, Kubeflow, Airflow, etc.)

Experience with LLMs, embeddings, vector search, or multimodal models

Experience in building scalable AI APIs and microservices, build APIs and ML services for deploying models in a high-availability production environment