Machine Learning Engineer, (Applied Machine Learning), AI & Data Platforms at Apple

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

15 Jun, 26

Salary

0.0

Posted On

17 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative AI, Applied Machine Learning, Backend Development, Platform Design, System Optimization, High Availability, Scalability, Reliability, RESTful APIs, Python, Privacy-Preserving Generation, Efficient Inference, Multimodal Integration, Production-Grade Systems, Microservices Architecture, Distributed Systems

Industry

Computers and Electronics Manufacturing

Description

Imagine what you could do here. At Apple, revolutionary ideas have a way of becoming extraordinary products, services, and customer experiences. Join the Ai Data Platform Applied Machine Learning team to pioneer enterprise solutions where generative AI meets Apple's unique commitment to privacy-first innovation. Together, we'll create tools that redefine industries while safeguarding what matters most – our users' trust. DESCRIPTION As a pivotal member of Apple’s enterprise generative AI efforts, you will help design, build, and evolve platforms and applications that power high-impact AI experiences across the company. You will contribute to the architecture and optimization of systems built for high availability, scalability, and reliability, working across backend services and application layers. Our team designs and implements scalable RESTful APIs, services, and platform components primarily using Python. We tackle unique challenges in privacy-preserving generation, efficient inference, and multimodal integration, while enabling teams to build on top of our foundations. We deliver production-grade systems and models that meet Apple’s rigorous standards for quality, performance, and scalability. MINIMUM QUALIFICATIONS Bachelor of Science in Computer Science, Machine Learning, or a related quantitative field or equivalent experience 2+ years of hands-on experience in machine learning and/or backend development in industry PREFERRED QUALIFICATIONS MS in Computer Science, Machine Learning, or a related quantitative field Experience with microservices architecture and distributed systems Experience in ML frameworks (PyT orch, JAX) for training, fine-tuning, and deploying ML/generative models at scale Proven track record of building enterprise-grade ML pipelines (data prep, distributed training, optimization, monitoring) in cloud environments (AWS, GCP , Azure) or on-prem infrastructure

Responsibilities

The role involves designing, building, and evolving enterprise platforms and applications that power high-impact AI experiences, focusing on architecture and optimization for scalability and reliability across backend services and application layers. Responsibilities include implementing scalable RESTful APIs and services primarily using Python to tackle challenges in privacy-preserving generation and efficient inference.