Senior ML Systems Engineer – Distributed Training

AI Breaking Wire; San Francisco (CA); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Equity

Health benefits

Remote-friendly US culture

Learning stipend

Job summary

Anthropic is seeking a Senior ML Engineer to join the Core Systems team to optimize training and inference infrastructure for the Claude family of foundation models. You will design high-performance distributed pipelines and work with researchers to remove scaling bottlenecks.

Ideal candidates have 5+ years of ML infrastructure experience, expert C++/Python skills, and hands-on work with AWS/GCP and Kubernetes.

Qualifications

• 5+ years of software engineering experience with a focus on large-scale ML infrastructure.
• Expert-level C++ and Python programming.
• Deep familiarity with distributed training paradigms (FSDP, Tensor Parallelism, Pipeline Parallelism).

Responsibilities

• Architect and implement high-performance distributed training and inference pipelines for massive transformer models.
• Collaborate with researchers to unblock scaling bottlenecks and improve hardware utilization.
• Develop low-latency inference runtimes and model optimization techniques (quantization, pruning, kernel fusion).
• Monitor and triage large-scale cluster performance issues across heterogeneous GPU clusters.

Skills

C++

Python

Distributed ML

Kubernetes

AWS / GCP

Tools

PyTorch

TensorFlow

Job description

Anthropic is seeking a Senior ML Engineer to join the Core Systems team to optimize training and inference infrastructure for the Claude family of foundation models. You will design high-performance distributed pipelines and work with researchers to remove scaling bottlenecks.

Ideal candidates have 5+ years of ML infrastructure experience, expert C++/Python skills, and hands-on work with AWS/GCP and Kubernetes.