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Machine Learning Engineer, (Applied Machine Learning), AI & Data Platforms (AiDP)Apple • United States
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Machine Learning Engineer, (Applied Machine Learning), AI & Data Platforms (AiDP)

Apple
  • US
    United States
  • US
    United States
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À propos

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.
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.
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\nBachelor of Science in Computer Science, Machine Learning, or a related quantitative field or equivalent experience
Strength in coding languages such as Python, Java, or GO.\nMS in Computer Science, Machine Learning, or a related quantitative field\nExperience with microservices architecture and distributed systems\nExperience in ML frameworks (PyTorch, JAX) for training, fine-tuning, and deploying ML/generative models at scale\nProven track record of building enterprise-grade ML pipelines (data prep, distributed training, optimization, monitoring) in cloud environments (AWS, GCP, Azure) or on-prem infrastructure
  • United States

Compétences linguistiques

  • English
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