Lead Machine Learning Engineer, Llm Infrastructure

Salesforce

San Francisco, California, United States
Base: $172,500 - $260,100 annually; base: $207,800...
Llm post-training infrastructure
Scalable pipelines for training orchestration
Feedback-driven model improvement systems
You will own the infrastructure and engineering systems that support LLM post-training, large-scale evaluation, and model deployment

Job Summary

  • You will own the infrastructure and engineering systems that support LLM post-training, large-scale evaluation, and model deployment.
  • This is an engineering-first role focused on ML infrastructure, distributed systems, and training/evaluation workflows rather than developing new model architectures or algorithms.
  • Competitive compensation, benefits, and strong long-term growth opportunities.

Matching Summary

You will own the infrastructure and engineering systems that support LLM post-training, large-scale evaluation, and model deployment.

Salary

Base: $172,500 - $260,100 annually; Base: $207,800 - $285,800 annually in select cities; Bonus/Equity: Not specified; Benefits: Not specified

Skills & Requirements

Must-have

  • LLM post-training infrastructure
  • Scalable pipelines for training orchestration
  • Feedback-driven model improvement systems
  • Distributed and GPU-based workloads
  • Python production systems

Nice-to-have

  • Agent-based learning support
  • Iterative model improvement systems
  • AI research incubation teams

Key Requirements

  • 5+ years of experience
  • Python proficiency
  • Hands-on ML infrastructure experience
  • Experience with LLM post-training workflows
  • Familiarity with cloud platforms and containerization

Work Rights

Not specified

Tailored Resume

Cover Letter