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Machine Learning Engineer - Video Generation Models

Apple· Machine Learning and AI
Apply on company site
Hybrid (San Francisco Bay Area)$150.4k - $277.6kfull-timePosted 1mo ago

About the role

Machine learning engineer with hands-on experience training large generative models to build video generation models. Responsibilities span pre-training, fine-tuning, and inference optimization, including designing training recipes, running distributed training, and making models efficient for production, with a focus on reproducibility and reliability.

Responsibilities

  • Pre-training video generation models, including architecture selection, training recipe design, hyperparameter and scaling decisions, and evaluation of model quality
  • Running, monitoring, and debugging large-scale distributed training jobs, and diagnosing loss instabilities, divergence, and throughput regressions
  • Improving training efficiency and cost, including parallelism strategy, mixed-precision training, checkpointing, and hardware utilization
  • Improving inference efficiency through step distillation, few-step sampling, and quantization, and characterizing the resulting quality and latency trade-offs
  • Adapting pre-trained models through fine-tuning, preference optimization, and knowledge distillation
  • Building and maintaining the training and evaluation code the team depends on, with an emphasis on reproducibility and reliability
  • Partnering with product and research stakeholders to translate requirements into modeling and engineering tasks

Qualifications

  • Bachelor's degree in Electrical Engineering, Computer Science, Computer Engineering, or relevant degree, and a minimum of 3 years relevant industry experience
  • Experience with large-scale generative model training for video generation
  • Experience running distributed training across multi-node GPU clusters
  • Strong software engineering skills in Python, with proficiency in a modern deep learning framework such as PyTorch or JAX
  • MS or PhD in Electrical Engineering, Computer Science, or Computer Engineering
  • Experience with video generation architectures, including diffusion or autoregressive models, temporal consistency, and long-horizon generation
  • Experience contributing to major foundation or base model pre-training efforts, including scaling laws and transferring training recipes across model and training scales
  • Experience with large-scale training operations, including parallelism strategies and diagnosing loss instability, divergence, or throughput regressions
  • Experience improving and adapting trained models, such as step distillation, few-step sampling, or quantization for inference efficiency, and supervised fine-tuning, preference optimization, or knowledge distillation for quality
  • Ability to work through ambiguity, collaborate across teams and disciplines, and communicate complex technical results clearly

Skills

Required:Distributed trainingPyTorch or JAXPython
Nice to have:Video generation architectures (diffusion/autoregressive)

Benefits

  • Apple benefits (medical and dental coverage, retirement benefits, discounted products and free services)
  • Educational reimbursement for advancing your career
  • Discretionary bonuses or commission payments and relocation eligibility
  • Apple shareholder opportunities through stock programs
  • Tuition reimbursement and related educational assistance
Last updated Sep 11, 2026. Interested? Apply on the company site.

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