Senior ML Infrastructure Engineer - VE Algorithms
Apple · San Diego, CA · Machine Learning and AI
About this role
Apple is hiring a senior-level ML Platform Engineer in the machine learning function based in San Diego, CA. The posting calls out experience with Python, PyTorch, LLMs, Data Structures and roughly 3+ years of relevant work. Listed education preference: a bachelor's degree or equivalent.
- Role
- ML Platform Engineer
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Location
- San Diego, CA
- Experience
- 3+ years
- Education
- Bachelor's degree
- Department
- Machine Learning and AI
- Posted
- Apr 21, 2026
Job description
from Apple careersAre you passionate about groundbreaking modeling technologies to enrich billions of people? We are the Video Engineering (VE) team at Apple developing cutting-edge video and machine learning algorithms to build the photo and video features that Apple devices are well known for. We are seeking engineers experienced in building infrastructure for training, adapting and deploying large-scale generative models. In this role, you will be working closely with a cross functional team of algorithm design and infrastructure engineers to benchmark, prototype and steer algorithmic choices to best fit our training and deployment infrastructure.
In this role you will be technically hands on, with deep subject matter expertise in ML infrastructure, focusing on distributed and parallelized training of images and videos, and efficient utilization of training hardware.
<h3>Minimum Qualifications</h3>BS in Electrical Engineering/Computer Science or a related field, with a focus on machine learning and minimum 3 years industry experience.
Experience in training and adapting LLMs.
Advanced fluency in PyTorch.
Excellent programming skills in Python or C++ and experience contributing software to large projects.
Experience with distributed training of large models.
<h3>Preferred Qualifications</h3>Strong Machine Learning fundamentals.
Experience working with large cross-functional and diverse teams.