Senior Machine Learning Engineer - Machine Learning Infrastructure
FlipFull Time
Senior (5 to 8 years)
San Francisco, California, United States
Candidates should have 6+ years of relevant industry experience, demonstrated experience as a technical lead to deliver projects end to end, strong Python expertise, and considerable prior work history with at least one statically typed language (such as Golang). Experience with modern ML frameworks like PyTorch and Tensorflow is preferred, as is experience scaling ML systems and/or data infrastructure to workloads of petabyte+ scale. A PhD or Master’s degree in machine learning or a related discipline may be required.
As a Machine Learning Engineer, you will drive ML systems and platform engineering efforts, scaling training and inference systems, mentoring junior engineers, building libraries and services, leading technical initiatives from ideation to execution, and delivering industry-leading applied research solutions. You will also work across teams to manage project priorities, evaluate trade-offs, and optimize model performance through techniques like VLM finetuning, auto-labeling, and model-based filtering. Finally, you will contribute to acquiring, filtering, and sanitizing large-scale datasets for LLM/VLM pretraining.
AI system for video content understanding
Twelve Labs focuses on artificial intelligence and video understanding by developing a system that analyzes videos to extract key features like actions, objects, and speech. This information is transformed into vector representations, enabling fast semantic search within large video datasets. The company differentiates itself by providing a platform that is faster and more effective than many existing models, allowing developers and product managers to easily integrate its technology through an API. Twelve Labs aims to make all videos searchable, enhancing the way businesses utilize video content.