About this role

Architect and implement large-scale pipelines for video ingestion, metadata extraction, and indexing
Develop and fine-tune multimodal models for video embeddings, scene segmentation, and relevance ranking using PyTorch
Scale ML infrastructure on AWS, leveraging multi-GPU clusters and distributed training
Collaborate with Product and Operations teams to translate ML performance into business insights and cost implications

6+ years in ML engineering, with a focus on information retrieval, embedding systems, or data annotation pipelines.
Proven track record building scalable indexing and search infrastructure, including vector stores and similarity search algorithms.
Expertise in Python and PyTorch for core model development.
Hands-on experience with Hugging Face Transformers for multimodal embeddings and fine-tuning.
Working experience with video, computer vision, and multi-modal LLMs.
Strong analytical skills for dissecting performance in large distributed systems; familiarity with multi-GPU training and vector databases preferred.

Senior Machine Learning Engineer

Key skills