合成数据生成研究工程师

Explore, innovate, and leverage novel technologies, from internal and external publications, to improve the realism, diversity, controllability, and generalizability of image synthesis, including techniques to enhance appearance and geometric realism, conditional image generation based on specific conditions or constraints, such as metadata, text-based categories, image masks, or multiple input modalities, and controllable image generation with manipulation of specific attributes like style and appearance

Hands-on contribution to synthetic image generation using deep generative models, computer graphics, or physics-based simulation

Tech lead for development and launch of CV/ML solutions for generating and synthesizing images used in the training of AR/VR models and system design

Drive cross-functional collaborations with partner teams, including but not limited to, Reality Labs Research, simulation, data systems, and Meta Superintelligence Lab

Co-own strategic planning, OKR setting, and roadmap generation for synthetic data and other R&D initiatives

Contribute to recruitment, mentoring, onboarding, and supporting the professional development of ML engineers/scientists, interns, and contractors

Collaborate with other engineers and data scientists to develop and deploy machine learning solutions

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

PhD in Computer Science or a related field with published projects in the fields of synthetic data generation, machine learning, deep learning, and/or computer vision

5+ years of technical leadership experience driving medium to large-scale cross-functional R&D projects focused on machine learning and computer vision

Experience implementing computer vision algorithms and deep learning models in C++ and Python, including hands-on work with 3D geometry, image processing, or sensor fusion

Experience in communicating complex technical research to cross-functional audiences through written documents, design reviews, or conference presentations

Problem-solving and interpersonal skills and experience to lead technical projects independently

Demonstrated track record of peer-reviewed publications in computer vision or machine learning at venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, or equivalents

Experience in designing data collection protocols and quality control, manifested in solid contributions in constructing high-quality computer vision and machine learning datasets

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Individual compensation is determined by skills, qualifications, experience, and location.

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

PhD in Computer Science or a related field with published projects in the fields of synthetic data generation, machine learning, deep learning, and/or computer vision.