Lead Machine Learning Engineer, Llm Infrastructure

Salesforce

Base: $172,500 - $260,100 annually; base: $207,800...
Not specified
Python production systems
Ml infrastructure
Distributed systems
Salesforce is seeking a Lead Machine Learning Engineer for their AI Research Incubation Team, focusing on infrastructure for large language model (LLM) post-training and evaluation. The role emphasizes building scalable systems and pipelines, requiring strong engineering skills and collaboration with cross-functional teams

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.
  • Own the systems that turn research models into production AI capabilities.

Matching Summary

Match Score: 85

Salesforce is seeking a Lead Machine Learning Engineer for their AI Research Incubation Team, focusing on infrastructure for large language model (LLM) post-training and evaluation. The role emphasizes building scalable systems and pipelines, requiring strong engineering skills and collaboration with cross-functional teams.

Salary

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

Skills & Requirements

Must-have

  • Python production systems
  • ML infrastructure
  • distributed systems
  • GPU-based workloads
  • LLM post-training infrastructure
  • feedback-driven training workflows

Nice-to-have

  • AI research incubation
  • agent-based learning
  • iterative model improvement
  • cross-functional influence

Key Requirements

  • 5+ years software engineering experience
  • Hands-on ML infrastructure experience
  • Cloud platforms (AWS, GCP)
  • Containerized environments (Docker, Kubernetes)

Work Rights

Not specified

Tailored Resume

Cover Letter