Senior Machine Learning Engineer - Automation for Translation and Multilingual Intelligence

Apple • Cupertino, CA

2d

About The Position

The AI/ML Translation & Multilingual Intelligence team is seeking a Machine Learning Engineer to develop and improve machine learning automation and tooling, with a focus on scalable, robust, and efficient model automation pipelines. The role involves working with large quantities of data and applying deep learning methods to real-world problems, creating production-quality models at scale, and establishing ML CI/CD pipelines.

The engineer will develop automation pipelines and tools for training, evaluating, and deploying machine learning models for machine translation and related NLP tasks. They will optimize machine learning pipelines for distributed data processing, training and inference throughput, and efficiency, and collaborate with software engineers and quality engineering teams to integrate models into production systems.

Requirements

• At least 3 years of experience working with the ML lifecycle, model management, data processing, large distributed systems, and cloud computing.
• Proficient coding skills in Python.
• Experience with distributed computing technologies such as Spark, Ray, and Dask.
• Excellent communication and problem-solving skills.

Nice To Haves

• Experience with ML infrastructure tools such as vLLM, SGLang, TRT-LLM, Slime, or Megatron-LM.
• Hands-on machine learning experience with model fine-tuning, evaluation, experiment tracking, pipeline building, and deployment.
• Experience with LLMs or neural machine translation.
• Deep knowledge of machine learning frameworks and technologies such as NLP, MT, ASR, PyTorch, TensorFlow, JAX, and transformer architectures.

Responsibilities

• Develop automation pipelines and tools for training, evaluating, and deploying machine learning models for machine translation and related NLP tasks.
• Implement and optimize ML pipelines, emphasizing distributed data processing, training and inference throughput, and efficiency.
• Collaborate with software engineers and QE to integrate ML models into production systems.
• Build scalable, robust, and efficient model automation pipelines and tooling.
• Work with large quantities of data and apply deep learning methods to real-world problems.
• Create production-quality models at scale and set up ML CI/CD pipelines.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed