On-Device ML Engineer: LLMs, Retrieval & Personalization

Latitude

Cupertino (CA)

Híbrido

USD 190.000 - 270.000

Jornada completa

14 días+

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Descripción de la vacante

Apple is seeking a Machine Learning Engineer to design, train, fine-tune, and deploy transformer-based language models and on-device AI that power intelligent search and personalized experiences while preserving privacy. You will build semantic retrieval, embedding, reranking, and retrieval-augmented generation systems for high-quality AI-powered experiences.

You will collaborate with researchers, product managers, and engineers to bring research into production, optimizing models for latency,

Formación

  • Bachelor degree in Computer Science, ML, AI or related field.
  • Experience training, fine-tuning, deploying transformer-based models and LLMs.
  • Proficiency in Python and modern ML frameworks; on-device deployment experience.

Responsabilidades

  • Design, train, fine-tune, and deploy transformer-based language models and LLMs.
  • Develop on-device retrieval, embedding, reranking, and RAG systems.
  • Collaborate with engineers, researchers, PMs, and designers to productionize research.
  • Research model compression, distillation, quantization, and low-latency inference.

Conocimientos

Python
C/C++
PyTorch
JAX
TensorFlow
NLP
Knowledge distillation
On-device inference
Retrieval & ranking

Educación

Bachelor degree in Computer Science / ML / AI
Master's or Ph.D. in related field

Herramientas

PyTorch
JAX
TensorFlow
Edge AI frameworks

Descripción del empleo

Apple is seeking a Machine Learning Engineer to design, train, fine-tune, and deploy transformer-based language models and on-device AI that power intelligent search and personalized experiences while preserving privacy. You will build semantic retrieval, embedding, reranking, and retrieval-augmented generation systems for high-quality AI-powered experiences.

You will collaborate with researchers, product managers, and engineers to bring research into production, optimizing models for latency,

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