Senior Distributed ML/RL Training Systems Engineer

Apple Inc.; Zürich; On-site; CHF 140,000 - 190,000; Full time

Job summary

Apple Inc. is building the next generation of large-scale ML and RL training infrastructure for its foundation models.

The role focuses on TPU-based training with JAX, designing robust, scalable RL pipelines and distributed actor/learner architectures to accelerate experimentation. You will work across the full ML stack, from performance tuning and compiler optimization to cluster orchestration, with teams in New York, Seattle, and Cupertino.

Qualifications

• PhD or MSc in Computer Science, Computer Engineering or a closely related field.
• Strong proficiency with PyTorch or JAX and experience running training workloads on GPUs/TPUs.
• Solid understanding of distributed systems concepts (parallelism strategies, fault tolerance, synchronization).
• Experience developing or optimizing training loops, RL pipelines, or large-scale model-training frameworks.
• Strong software engineering skills in Python, with emphasis on reliability and high-performance execution.

Responsibilities

• Design, build, and scale RL training systems for large-scale foundation models.
• Develop robust, high‑performance RL pipelines supporting distributed actor/learner architectures.
• Optimize training workflows from low‑level performance tuning to cluster orchestration and resource management.

Skills

PyTorch

JAX

Distributed systems

Python

High‑performance ML

GPU/TPU workloads

Education

PhD or MSc in Computer Science

Tools

XLA

TPU v5/v6

Job description

Apple Inc. is building the next generation of large-scale ML and RL training infrastructure for its foundation models.

The role focuses on TPU-based training with JAX, designing robust, scalable RL pipelines and distributed actor/learner architectures to accelerate experimentation. You will work across the full ML stack, from performance tuning and compiler optimization to cluster orchestration, with teams in New York, Seattle, and Cupertino.