MTS/SMTS Software Engineer - ML Infrastructure

Salesforce is seeking a Staff-level Machine Learning Infrastructure Engineer to join their Einstein AI platform team. This role combines software engineering and machine learning expertise to build and scale AI services that power Salesforce's enterprise products. The Einstein platform currently handles over a billion predictions daily and trains thousands of models, including various Large Language Models (LLMs).

The position offers an opportunity to work on cutting-edge AI infrastructure that democratizes machine learning capabilities across Salesforce's product suite. You'll be responsible for designing and implementing scalable systems that support the entire ML lifecycle, from data processing to model training and deployment. The role involves working with modern cloud technologies, containerization, and distributed systems.

The ideal candidate brings deep technical expertise in both software engineering and machine learning operations, with the ability to build robust, production-grade systems. You'll collaborate with cross-functional teams including product managers, data scientists, and researchers to deliver innovative solutions that meet customer needs.

Salesforce offers competitive compensation with base salary ranging from $125,700 to $334,600 depending on location and experience. The company provides comprehensive benefits including medical, dental, vision, 401(k), and stock purchase programs. The work environment is flexible with hybrid options available across multiple locations including San Francisco, Seattle, and Palo Alto.

This is an excellent opportunity for experienced engineers who want to work on large-scale AI systems while contributing to Salesforce's mission of transforming how businesses connect with customers through AI-powered solutions.