Research Engineer (Research)

Location: London

Meta is seeking a Research Engineer to join our Large Language Model (LLM) Research team. We conduct focused research and engineering to build state-of-the-art LLMs, which we often open-source, like our team’s recent Llama 2. We are looking for engineers who have a background in generative AI and NLP, with experience in areas like language model evaluation; data processing for pre-training and fine-tuning; responsible LLMs; LLM alignment; reinforcement learning for language model tuning; efficient training and inference; and/or multilingual and multimodal modeling. Responsibilities
# Design methods, tools, and infrastructure to push forward the state of the art in large language models.
# Define research goals informed by practical engineering concerns.
# Contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results.
# Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
# Work with a large and globally distributed team.
# Contribute to publications and open-sourcing efforts.

Minimum Qualifications
# Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
# Research experience in machine learning, deep learning, and/or natural language processing.
# Experience with developing machine learning models at scale from inception to business impact.
# Programming experience in Python and hands-on experience with frameworks such as PyTorch.
# Exposure to architectural patterns of large scale software applications.
# Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications
# Master's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
# A PhD in AI, computer science, data science, or related technical fields.
# Direct experience in generative AI and LLM research.
# First author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).

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