Machine Learning Engineer

Overview

Machine Learning Engineer build and deliver ML models and pipelines for creative understanding across vision, video, and language.

What you'll do

• Own an ML problem from building through training, deployment, and iteration.
• Build and train models for creative understanding across vision, video, and language.
• Build labels and features using LLMs, subject-matter experts, and user activity data.
• Deliver ingestion, featurization, training, versioning, and inference pipelines at scale.
• Validate models using offline benchmarks and online A/B tests before release.
• Operate production ML on Spark, Kubernetes, and GPU/CPU environments.

What you'll need

• Master's degree and 5+ years relevant experience, or PhD with 2+ years (or equivalent impact).
• Shipped ML models to production with measurable results for a product or business.
• Strong Python and PyTorch for model development and deployment.
• Experience in deep learning across vision, video, NLP, or generative AI (LLM/VLM fine-tuning, embeddings, or RAG).
• End-to-end ML systems: feature engineering, training pipelines, inference, and production monitoring.
• Distributed data processing and cloud platforms including Spark and Kubernetes plus GCP, AWS, or Azure.
• Clear communication with cross-functional partners on ML trade-offs and technical direction.

Details

• Location: Bangalore.