Research Engineer, Computer Vision/Multimodal - Generative AI

Meta is seeking a Research Engineer with expertise in Computer Vision to join our Generative AI pillar.

We conduct in-depth research and engineering to build state-of-the-art foundational models, which we often open-source, like our team’s recently released Llama 4.

We push boundaries across multiple modalities (e.g., text, speech, image, video) and focus on critical domains such as pre-training, post-training, data training, safety, evaluation, agents, etc.

Responsibilities:

Research Engineer, Computer Vision/Multimodal - Generative AI Responsibilities:

Lead, collaborate, and execute on developing scalable and effective data curation, model development and eval systems that push forward the state of the art CV and multimodal research.

Work towards long-term ambitious research/development goals, while identifying intermediate milestones.

Directly contribute to experiments, including designing experimental details, building reusable code, running evaluations, and organizing results.

Drive innovation through seamless collaboration, collective problem-solving, and XFN initiatives.

Prioritize research and development that can be applied to Meta's product development.

Qualification and experience:

Minimum Qualifications:

2+ years of industry research or engineering experience.

Experience training large-scale Computer Vision or related AI models/datasets.

Fluent in Python and PyTorch (or equivalent).

Experience leading large scale AI/ML technical projects.

Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Preferred:

Preferred Qualifications:

Master or PhD degree in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, or relevant technical field.

Publication track record at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).

Experience solving complex problems and comparing alternative solutions, tradeoffs, and varied points of view to determine a path forward.

Experience working and communicating cross functionally in a team environment.