Machine Learning Scientist, Studio Media Algorithms
Job Description:
• Design, train/post-train/fine-tune, and evaluate foundational algorithmic solutions with applications in a variety of domains in the VFX, animation, and games space
• Develop reusable foundational components and best practices, such as dataset curation, large-scale training, and post-training processes
• Work cross-functionally with engineers, scientists, artists, and product leaders to help identify and prioritize strategic research investment opportunities and problem requirements
• Expand technical depth and domain expertise into new/adjacent areas as the business needs and the state of technology evolve
Requirements:
• Research experience with a successful track record of delivering quality results and/or academic publications in top ML, CV, CG, or NLP venues
• Deep familiarity with modern generative model architectures, including diffusion models (e.g., MMDiT) and/or autoregressive models (e.g., GPT-style)
• Experience with the full stack of model development: data curation, annotation/captioning, distributed training, post-training techniques (e.g., fine-tuning, RL), and/or robust evaluation
• Expertise in designing and training deep learning (DL) architectures for media understanding and generation
• Deep mathematical skills with knowledge of statistical methods and optimization
• Extensive experience with DL frameworks such as Tensorflow or PyTorch
• Strong programming skills in languages such as Python, Java, or C++
• Advanced degree in Computer Science or related field
Benefits:
• Inclusion is a Netflix value
• Flexible work arrangements
• Design, train/post-train/fine-tune, and evaluate foundational algorithmic solutions with applications in a variety of domains in the VFX, animation, and games space
• Develop reusable foundational components and best practices, such as dataset curation, large-scale training, and post-training processes
• Work cross-functionally with engineers, scientists, artists, and product leaders to help identify and prioritize strategic research investment opportunities and problem requirements
• Expand technical depth and domain expertise into new/adjacent areas as the business needs and the state of technology evolve
Requirements:
• Research experience with a successful track record of delivering quality results and/or academic publications in top ML, CV, CG, or NLP venues
• Deep familiarity with modern generative model architectures, including diffusion models (e.g., MMDiT) and/or autoregressive models (e.g., GPT-style)
• Experience with the full stack of model development: data curation, annotation/captioning, distributed training, post-training techniques (e.g., fine-tuning, RL), and/or robust evaluation
• Expertise in designing and training deep learning (DL) architectures for media understanding and generation
• Deep mathematical skills with knowledge of statistical methods and optimization
• Extensive experience with DL frameworks such as Tensorflow or PyTorch
• Strong programming skills in languages such as Python, Java, or C++
• Advanced degree in Computer Science or related field
Benefits:
• Inclusion is a Netflix value
• Flexible work arrangements