Software Engineer - Machine Learning Infrastructure, Slack

Salesforce

Base: $164,000 - $313,700 annually; bonus/equity: ...
Build and operate distributed systems
Kubernetes and container based platforms
Modern ml infrastructure and serving stacks
The AI and ML Infrastructure team is responsible for the foundational systems that enable machine learning and AI across the company, designing, building, and operating reliable, scalable, and high-performance platforms

Job Summary

  • The AI and ML Infrastructure team is responsible for the foundational systems that enable machine learning and AI across the company, designing, building, and operating reliable, scalable, and high-performance platforms.
  • 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, designing, building, and operating reliable, scalable, and high-performance platforms.

Salary

Base: $164,000 - $313,700 annually; Bonus/Equity: company bonus, incentive for sales roles, equity; Benefits: medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), employee stock purchasing program

Skills & Requirements

Must-have

  • Build and operate distributed systems
  • Kubernetes and container based platforms
  • Modern ML infrastructure and serving stacks
  • GPU infrastructure performance optimization
  • Cloud native systems on public cloud
  • Design and architecture documentation

Nice-to-have

  • AI-powered operating system
  • Transform how people work
  • Seamless, consumer-grade AI experience
  • Architectural decisions for large scale systems
  • Thought leadership through engineering blog posts

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
  • A related technical degree required

Work Rights

Not specified

Tailored Resume

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