Senior Machine Learning Engineer

Salesforce AI Research is looking for a Machine Learning Engineer to incubate next-generation agentic AI platform. You will work with research scientists, software engineers, product managers and solution engineers closely to design, implement and iterate agentic AI systems with customers. With your strong technical competence, strategic thinking and customer engagement, you will innovate at the frontier of the field, having the opportunity to create new solutions and define new categories of product with meaningful impact to Salesforce customers and beyond. We are looking for candidates who

• Has exceptional engineering skills.
• Has deep ML knowledge with meaningful implementation track records.
• Prioritize deep and strategic thinking.
• Has dedication, patience and resilience to build exceptional product experience.
• Collaborative and win with teams.
• Proactive and bias to action, comfortable in fast-pacing environment.
• For this role, we mainly look for BS/MS student instead of PHD student (For PhD, only look for candidate who fulfill one of the 5 criteria below, and interested in MLE instead of RS role)
• Top school majoring in CS (Stanford, Berkeley, CMU, MIT)
• Competitive coding winner (ACM-ICPC, etc). Look for global and competitive competition, Kaggle dose not count.
• Startup founders in agentic AI, LLM, area (e.g., YC backed startup)
• As first contributor, open source and maintain projects that gets traction (2k+ stars)
• For BS/MS, as first author, publish at least one high-impact paper (500+ citations). For PhD, the bar will be higher (2-3 first-author high impact (500+ citations) papers or 1 first-author stellar (3000+citations) paper)

Required Skills

Programming & Systems

• Strong proficiency in Python; solid experience with C++ and/or Java
• Strong software engineering fundamentals (data structures, algorithms, system design)
• Experience building production-quality systems Agentic / LLM Systems
• Practical experience with LLMs and agentic workflows (tool use, planning, memory, multi-step reasoning)
• Experience building end-to-end AI agents or complex AI-driven applications
• Familiarity with prompting, orchestration, and evaluation for LLM-based systems Machine Learning & AI
• Hands-on experience with deep learning frameworks
• Strong understanding of ML fundamentals
• Experience implementing and debugging model training, evaluation, and inference pipelines Infrastructure & Deployment
• Experience deploying ML systems using Docker and cloud platforms (AWS, GCP, or Azure)
• Familiarity with distributed training or inference and performance optimization

Additional Information

• The typical base salary range for this position is $148,500 - $223,900 annually
• In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $246,000 annually
• The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits