Machine Learning Infrastructure Engineer at Apple

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

05 Feb, 26

Salary

0.0

Posted On

07 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Engineering, Python, Cloud Computing, Kubernetes, CI/CD, Infrastructure as Code, Distributed Data Processing, Model Training, Data Preprocessing, Communication Skills, Problem Solving, Software Integration, Networking, Storage, Containers

Industry

Computers and Electronics Manufacturing

Description

Want to ship amazing experiences in Apple products? Be part of the team in the Video Computer Vision (VCV) organization that focuses on people understanding from real-time video streams and building higher level reasoning algorithms. VCV delivered features such as Face ID, RoomPlan as well as many other computer vision algorithms powering Apple Vision Pro, iPhone, and iPad. We focus on a balance of research and development to deliver Apple quality, pioneering experiences. Come shape Apple products as a driven and dedicated ML Infrastructure and Data Engineer to push the limits of ML algorithms with hands-on work and real world and simulated data, in an innovative team and be part of building the next big thing. DESCRIPTION As part of the Video Computer Vision (VCV) team, you will help us create the data and infrastructure ecosystem needed to support our ML development and continuously improve our features. We take full end-to-end ownership of our services and data products, driving them through every stage meticulously, encompassing conception, design, implementation, deployment, and maintenance. As a result, each one of us takes our responsibilities seriously. In this team, you’ll have the opportunity to work on complex problems in close partnership with our ML engineers, data scientists and software integration teams. MINIMUM QUALIFICATIONS Bachelor's degree in Computer Science or related discipline, and 2 years relevant industry experience. Strong foundational knowledge in Computer Science. Extensive programming experience in Python. Hands-on experience with cloud providers (AWS, GCP, or Azure). Strong understanding of core infrastructure concepts (e.g., compute, networking, storage, containers, Kubernetes). PREFERRED QUALIFICATIONS Experience with machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment. Proficiency with cloud computing and distributed data processing infrastructure and tools (e.g., Ray, Spark, Trino). Hands-on experience with CI/CD pipelines and practices. Familiarity with Infrastructure as Code (IaC) tools (e.g. Terraform, Pulumi, or CloudFormation). Experience building on LLMs or other generative models. Ability to drive projects from concept to production, balancing business needs with technical quality and timely delivery. Excellent communication skills, ability to work both independently and multi-functionally.

Responsibilities

You will help create the data and infrastructure ecosystem needed to support ML development and improve features. The role involves end-to-end ownership of services and data products, from conception to maintenance.