At Reality Labs Research (RL-R), our goal is to explore, innovate and design novel interfaces and hardware subsystems for the next generation of virtual, augmented, and mixed reality experiences. We are driving research towards a vision of an always-on augmented reality device that can enable high-quality contextually relevant interactions across a range of complex, dynamic, real-world tasks in natural environments; to achieve this goal, our team draws on and fundamentally advances methods and knowledge from artificial intelligence, multimodal machine learning, computer vision, and signal processing. We are looking for a skilled and motivated research engineer with expertise in multimodal data lifecycle (i.e., from collection, model training, to model evaluation and benchmarking). More broadly, the chosen candidate will work with a diverse and highly interdisciplinary team of researchers and engineers and will have access to cutting edge technology, resources, and testing facilities.

• Collaborate with leadership to define functional requirements and key performance indicators for models, ensuring alignment with research goals and multimodal context understanding.
• Drive the design, implementation, and management of the offline data pipeline for model training and benchmarking, focusing on rigorous multimodal data collections (e.g., vision, audio, eye gaze, IMU, etc.) to push forward model performance.
• Work closely with other Research Scientists on offline and online system benchmarking and develop regular reports of the system shortcomings and performance across the functional requirements.

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• 2+ years of experience developing end-to-end ML/data pipelines with a focus on dataset preprocessing and model benchmarking.
• 2+ years of experience experience writing software (Python and C/C++) and executing complex machine learning experiments.
• Research experience in one or more of these areas: NLP, Computer Vision, Multimodal, Speech.

• PhD degree or equivalent experience in Computer Science, Mathematics, Engineering or a related field.
• Publication record in machine learning, AI, computer science, statistics, applied mathematics, data science, or related technical fields.
• Programming experience in Python and hands-on experience with frameworks such as PyTorch.