Senior/staff Software Engineer- Machine Learning Infrastructure, Slack

Salesforce

Multiple Locations
Base: $172,500 - $313,700 annually; bonus/equity: ...
Ml model training and serving
Kubernetes and container platforms
Gpu infrastructure management
The AI and ML Infrastructure team is responsible for the foundational systems that enable machine learning and AI across the company, owning shared infrastructure, services, and tooling that support the full ML lifecycle

Job Summary

  • The AI and ML Infrastructure team is responsible for the foundational systems that enable machine learning and AI across the company, owning shared infrastructure, services, and tooling that support the full ML lifecycle.
  • In this role, you will own foundational infrastructure for large scale model training and inference, and evolve it into a reliable, secure, and self service platform used across the company.
  • Salesforce offers a variety of benefits to help you live well including time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program.

Matching Summary

The AI and ML Infrastructure team is responsible for the foundational systems that enable machine learning and AI across the company, owning shared infrastructure, services, and tooling that support the full ML lifecycle.

Salary

Base: $172,500 - $313,700 annually; Bonus/Equity: Not specified; Benefits: Medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), employee stock purchasing program

Skills & Requirements

Must-have

  • ML model training and serving
  • Kubernetes and container platforms
  • GPU infrastructure management
  • Distributed systems engineering
  • Cloud-native systems on public cloud

Nice-to-have

  • AI-powered operating system
  • Consumer-grade AI experience
  • Agentic era workforce transformation
  • Developer facing tools and SDKs

Key Requirements

  • Significant professional experience in software engineering
  • Deep experience building and operating distributed systems
  • Hands on experience with modern ML infrastructure
  • Experience working with GPU infrastructure
  • Strong experience with data infrastructure and orchestration
  • Experience building and operating cloud native systems
  • Related technical degree required

Work Rights

Not specified

Tailored Resume

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