Machine Learning Engineer - Video Generation Models

Apple Inc.; San Diego (CA); On-site; USD 142,000 - 263,000; Full time

Job summary

Apple Inc. in San Diego is seeking a machine learning engineer to advance video generation models from pre-training to efficient inference. You will design training recipes, manage large distributed runs, and push for reproducible, production-ready code across Apple teams.

The role emphasizes hands-on experience with large generative models for video, distributed GPU clusters, and proficiency in Python with PyTorch or JAX. Collaboration with researchers and product teams is key.

Qualifications

• Bachelor's degree in EE/CS/CE or related field with 3+ years of industry experience.
• Experience training large generative models for video generation.
• Experience running distributed training on multi-node GPU clusters.
• Proficiency in Python with PyTorch or JAX.

Responsibilities

• Pre-training video generation models, including architecture decisions and training recipe design.
• Run, monitor, and debug large-scale distributed training jobs and diagnose issues.
• Improve training efficiency with parallelism, mixed-precision, checkpointing and hardware utilization.
• Improve inference efficiency through distillation, sampling, and quantization.
• Adapt pre-trained models via fine-tuning and knowledge distillation.
• Build and maintain training and evaluation code with emphasis on reproducibility.
• Partner with product and research teams to translate requirements into modeling tasks.

Skills

Python programming

Distributed training

Large-scale training experience

Education

Bachelor's degree in Electrical Engineering, Computer Science, Computer Engineering, or relevant degree

Tools

PyTorch

JAX

Job description

San Diego Metro Area, California, United States Machine Learning and AI

We are hiring a machine learning engineer with deep, hands-on experience training large generative models to help build our video generation models. You will work across pre-training, fine-tuning, and inference optimization, from designing the training recipe and running large distributed training jobs through making the resulting models efficient to run. As a member of the team, you will develop fundamental model capabilities and collaborate with engineers and researchers across Apple to advance our products.

Description

As a member of our fast-paced group, you'll have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for someone who has taken large generative models through the full lifecycle, from pre-training through fine-tuning and efficient inference, and can bring that depth to video, with the engineering skills to make that work reproducible and production-ready.

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

Minimum 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

Preferred Qualifications

• 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

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $142,300 and $263,300, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.