Senior ML Engineer - Translation Automation & Multilingual AI

Apple, Inc.; Cupertino (CA); Presencial; USD 150.000 - 278.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Relocation assistance

Tuition reimbursement

Stock purchase program

Descripción de la vacante

Apple, Inc. in Cupertino, California is seeking a Senior Machine Learning Engineer to drive automation for translation and multilingual intelligence. You will develop scalable model automation pipelines, train and deploy NLP models, and work with cross‑functional teams to deliver production‑grade ML systems.

The role emphasizes building robust ML CI/CD, optimizing pipelines, and applying state‑of‑the-art deep learning techniques to large datasets in a production environment.

Formación

• 3+ years ML lifecycle, model management, data processing, large distributed systems and cloud computing (Spark, Ray, Dask).
• Proficient in Python; experience with ML infra tools such as vLLM, SGLang, TRT-llm, Slime, Megatron-LM.
• Excellent communication and problem-solving skills.

Responsabilidades

• Develop automation pipelines and tools for training, evaluating and deploying ML models for machine translation and related NLP tasks.
• Implement and optimize ML pipelines with emphasis on distributed data processing, training, inference throughput and efficiency.
• Collaborate with software engineers and QE to integrate ML models into production systems.

Conocimientos

ML lifecycle

Model management

Data processing

Distributed systems

Spark

Ray

Dask

Python

ML infra tools

Communication

Problem solving

LLMs

Neural machine translation

NLP

PyTorch

TensorFlow

JAX

Transformers

Herramientas

vLLM

SGLang

TRT-llm

Slime

Megatron-LM

Descripción del empleo

Apple, Inc. in Cupertino, California is seeking a Senior Machine Learning Engineer to drive automation for translation and multilingual intelligence. You will develop scalable model automation pipelines, train and deploy NLP models, and work with cross‑functional teams to deliver production‑grade ML systems.

The role emphasizes building robust ML CI/CD, optimizing pipelines, and applying state‑of‑the-art deep learning techniques to large datasets in a production environment.