Staff ML Engineer: Scalable Training Platform

Apple Inc.; Seattle (WA); On-site; USD 175,000 - 309,000; Full time

Job summary

Apple Inc. is seeking a Staff ML/Research Engineer for Apple Cloud AI in Seattle. You will drive large-scale model training, develop training recipes for pre-training, fine-tuning, RL, and distillation, and set direction across teams to improve efficiency and quality.

You will work with researchers to deploy techniques like parameter-efficient fine-tuning, quantization-aware training, and teacher-student distillation, while ensuring privacy and security in training runs across GPUs/TPUs.

Qualifications

• 8+ years of experience in large-scale model training, including reinforcement learning, from research to production.
• 5+ years of experience building and operating large-scale model training systems in production.
• Experience with common fine-tuning and distillation techniques, such as supervised fine-tuning, parameter-efficient fine-tuning with LoRA, and teacher-student distillation.
• Hands-on experience with at least one higher-level training framework such as Megatron-LM, DeepSpeed, TorchTitan, NeMo, AXLearn, or MaxText.
• Deep expertise in PyTorch or JAX, including distributed training features.
• Strong programming skills in Python or C++.
• BS, MS, or PhD degree in Computer Science, Computer Engineering, or equivalent practical experience

Responsibilities

• Work with researchers and ML engineers to develop cutting-edge ML models, and turn their needs into training features and performance improvements that every team on the platform can use.
• Develop model distillation and compression methods, such as teacher-student distillation and quantization-aware training, that bring the quality of large models to smaller models.
• Train models with long-context extension, mixture-of-experts architectures, and multimodal inputs, and solve the stability and efficiency problems each one brings.
• Dig into training behavior at scale, such as loss spikes, divergence, and drops in throughput, and track each problem down to its root cause in the data, the numerics, the code, or the hardware.
• Build and own scalable, efficient training frameworks and services on GPUs and TPUs, built on PyTorch or JAX and on higher-level frameworks.
• Build reinforcement learning infrastructure for post-training, including rollout and inference services, reward pipelines, and secure sandboxes where models can run code and use tools.
• Integrate the training platform with Apple's data and governance stack so that every training run meets privacy and security standards.
• Set technical direction across teams, mentor engineers, and raise the engineering bar.

Skills

Large-scale training

Reinforcement learning

Fine-tuning

Distillation

Megatron-LM

PyTorch

Python

C++

Distributed training

Education

BS/MS/PhD in CS/CE

Tools

Megatron-LM

DeepSpeed

TorchTitan

NeMo

AXLearn

MaxText

Job description

Apple Inc. is seeking a Staff ML/Research Engineer for Apple Cloud AI in Seattle. You will drive large-scale model training, develop training recipes for pre-training, fine-tuning, RL, and distillation, and set direction across teams to improve efficiency and quality.

You will work with researchers to deploy techniques like parameter-efficient fine-tuning, quantization-aware training, and teacher-student distillation, while ensuring privacy and security in training runs across GPUs/TPUs.