Software Engineer (multiple Levels) - Machine Learning Infrastructure, Slack

Salesforce Service Cloud

Base: $148,500 - $313,700 annually; bonus/equity: ...
Not specified (potentially hybrid or fully remote based on common practices in tech).
Distributed systems architecture
Kubernetes and container orchestration
Gpu infrastructure management
Salesforce is seeking Software Engineers at various levels to join their Machine Learning Infrastructure team within Slack, focusing on building reliable AI systems. The ideal candidates should have significant experience in software engineering, particularly with distributed systems and modern ML infrastructure, while also possessing strong communication skills

Job Summary

  • The role involves architecting and operating foundational systems for large-scale model training and inference within Slack's AI ecosystem.
  • Candidates must possess deep expertise in Kubernetes, GPU infrastructure, and modern ML stacks like Ray, KubeRay, and vLLM.
  • Salesforce offers a competitive base salary range of $148,500 to $313,700 annually along with comprehensive benefits including equity and medical coverage.

Matching Summary

Match Score: 85

Salesforce is seeking Software Engineers at various levels to join their Machine Learning Infrastructure team within Slack, focusing on building reliable AI systems. The ideal candidates should have significant experience in software engineering, particularly with distributed systems and modern ML infrastructure, while also possessing strong communication skills.

Salary

Base: $148,500 - $313,700 annually; Bonus/Equity: Not specified; Benefits: Medical, dental, vision, 401(k), paid parental leave, stock purchasing program

Skills & Requirements

Must-have

  • Distributed systems architecture
  • Kubernetes and container orchestration
  • GPU infrastructure management
  • Ray or KubeRay experience
  • vLLM model serving
  • Cloud native platform development
  • AI prompt engineering

Nice-to-have

  • Technical leadership and mentorship
  • Experience with Airflow and Spark
  • Asynchronous global team collaboration
  • AI-first engineering approach
  • Thought leadership in engineering blogs

Key Requirements

  • Related technical degree required
  • Significant professional software engineering experience
  • Expert level knowledge of Kubernetes
  • Hands-on experience with GPU optimization
  • Demonstrated AI-first engineering mindset

Work Rights

Not specified

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