Research Engineer (Robotics) - World Modelling, FAIR

Meta is seeking a Research Engineer to join their prestigious Fundamental AI Research (FAIR) team, one of the leading industrial AI research organizations globally. This role focuses on building world models for understanding and predicting physical world interactions, particularly from video data, and developing efficient algorithms for world model-based planning and control.

The position is part of an ambitious initiative to train and utilize world models for embodied and wearable agents. The team works across various cutting-edge areas including self-supervised learning from video (such as joint-embedding predictive architectures/JEPAs), predictive models, model-based reinforcement learning, and model-predictive control. The role involves innovation across the entire stack, from data curation to training large-scale state-of-the-art models and designing robust benchmarks.

As a Research Engineer, you'll be at the forefront of AI innovation, working with a cross-functional team of scientists and engineers. The role combines advanced research with practical engineering, requiring expertise in machine learning, robotics, and software development. You'll contribute to experimental design, implementation, and evaluation while also building optimized software tooling and infrastructure to accelerate research outcomes.

The position offers competitive compensation ranging from $85,100 to $251,000 annually, plus bonus and equity opportunities. Meta provides comprehensive benefits and the opportunity to work with world-class researchers and engineers. The role is available in either Seattle, WA or New York, NY, offering the chance to work in major tech hubs while contributing to groundbreaking AI research that could shape the future of technology.

This is an ideal opportunity for someone with strong technical skills, research experience, and a passion for pushing the boundaries of AI and robotics. The role requires both theoretical knowledge and practical engineering skills, making it perfect for candidates who enjoy bridging the gap between cutting-edge research and real-world applications.