Machine Learning Engineer, (Applied Machine Learning), AI & Data Platforms (AiDP)

Apple • Sunnyvale, CA

5h

About The Position

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 models, platforms, and applications that power
high-impact AI experiences across the company. You will contribute to the
architecture and optimization of AI/gen AI systems built for high availability,
scalability, and reliability, working across backend services and application
layers. Our team designs and implements SOTA AI Models, scalable RESTful APIs,
services, and platform components that advance adoption of gen AI at apple. We
tackle unique challenges in AI Safety, privacy-preserving generations, 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.

Requirements

• 2+ years of hands-on experience in machine learning or backend development in industry OR 3+ years of hands on research and development experience in academia
• Bachelor of Science in Computer Science, Machine Learning, or a related quantitative field or equivalent experience

Nice To Haves

• Strength in coding languages such as Python, Java, or GO.
• MS in Computer Science, Machine Learning, or a related quantitative field
• Experience with microservices architecture and distributed systems
• Experience in ML frameworks (PyTorch, 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level