Distributed Training Engineer

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

Not verified

401(k) match

Not verified

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Distributed Training Engineer Menlo Park, Remote, Menlo Park, California, USA About Periodic Labs We are an AI + physical sciences lab building state of the art models to make novel scientific discoveries. We are well funded and growing rapidly. Team members are owners who identity and solve problems without boundaries or bureaucracy. We eagerly learn new tools and new science to push forward our mission. About the role You will optimize, operate and develop large-scale distributed LLM training systems that power AI scientific research. You will work closely with researchers to bring up, debug, and maintain mid-training and reinforcement learning workflows. You will build tools and directly support frontier-scale experiments to make Periodic Labs the world's best AI + science lab for physicists, computational materials scientists, AI researchers, and engineers. You will contribute open-source large scale LLM training frameworks. You might thrive in this role if you have experience with: - Training on clusters with ≥5,000 GPUs - 5D parallel LLM training - Distributed training frameworks such as Megatron-LM, FSDP, DeepSpeed, TorchTitan - Optimizing training throughput for large scale Mixture-of-Expert models

Read the full description at jobs.ashbyhq.com. FewerJobs shows a preview and links to the original posting.