AI Research Engineer, VLLM (vision large language models) - Generative AI
Meta

Meta is seeking a Research Engineer to join our Llama Large Language Model (LLM) Research team. We are looking for recognized experts in VLLMs; with experience in areas like vision encoders, data filtering/curation for pre and post-training, RLHF, responsible AI and model controllability. The ideal candidate will have an interest in producing and applying new science/systems/technologies to help us develop and responsibly release vision large language models.

AI Research Engineer, VLLM (vision large language models) - 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 in multimodal reasoning and generation research.
• Work towards long-term ambitious research/development goals, while identifying intermediate milestones.
• Directly contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results.
• Work with a large team.
• Mentor other team members. Play a significant role in healthy cross-functional collaboration.
• Prioritize research and development that can be applied to Meta's product development.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Masters in AI, computer science, or related technical fields.
• 3+ years of Experience holding an industry, faculty, or government researcher position.
• Publications in machine learning, computer vision, NLP, Audio
• Experience writing software and executing complex experiments involving large AI models and datasets.
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications:

• Industry research & development experiences in generative AI and LLM research.
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
• Fluent in Python and PyTorch (or equivalent).
• Publication track record at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).
• PhD in AI, computer science, or related technical fields.

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