Senior Distributed ML Systems Engineer (Remote • Equity)

Pluralis Research; San Francisco (CA); Remote; Full time

Benefits offered by this job

Equity-heavy compensation

Competitive base salary

Visa sponsorship

Remote-first work model

Access to Melbourne hub

Job summary

A leading AI research company in San Francisco seeks Senior/Staff Engineers skilled in distributed systems and large-scale ML training. Responsibilities include designing systems optimized for low-bandwidth conditions and implementing robust training strategies. Ideal candidates will have over 5 years experience, expert-level Python skills, and familiarity with distributed training frameworks. The role offers equity-heavy compensation, a competitive salary, remote-first work culture, and a world-class team environment.

Qualifications

• 5+ years of experience in distributed systems and ML large-scale training.
• Expert-level Python with production experience.
• Experience with distributed training frameworks.

Responsibilities

• Design and implement large-scale distributed training systems.
• Develop model-parallel training strategies with custom techniques.
• Optimize GPU utilization and compute performance across nodes.

Skills

Distributed systems

Large-scale training

Model parallelism

Python programming

Networking fundamentals

GPU optimization

Tools

FSDP

DeepSpeed

Megatron

Job description

A leading AI research company in San Francisco seeks Senior/Staff Engineers skilled in distributed systems and large-scale ML training. Responsibilities include designing systems optimized for low-bandwidth conditions and implementing robust training strategies. Ideal candidates will have over 5 years experience, expert-level Python skills, and familiarity with distributed training frameworks. The role offers equity-heavy compensation, a competitive salary, remote-first work culture, and a world-class team environment.