Senior Member of Technical Staff, AI Research

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. 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 [... source excerpt omitted ...] nders in agentic AI, LLM, area (e.g., YC backed startup) Programming & Systems: Strong proficiency in Python; solid experience with C++ and/or Java Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code. Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale. Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables A [... source excerpt omitted ...] an or AI-generated) for correctness, quality, security, and performance 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 pi