Intern, AI Engineering

About Workato Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility. Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com. Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles . We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care . That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you! Also, feel free to check out why: Business Insider named us an “enterprise startup to bet your career on” Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America Quartz ranked us the #1 best company for remote workers Responsibilities We are seeking exceptional graduate students to join our AI Lab as Research Interns in San Francisco. You'll work on fundamental problems in LLM-based agentic systems and efficient AI infrastructure, with opportunities to publish your research while making direct impact on production systems serving enterprise customers. In this role, you will also be responsible to: Conduct original research on LLM agent architectures and optimization techniques Develop and evaluate novel algorithms with both academic rigor and production feasibility Present your work at internal research seminars and external conferences Mentor and collaborate with LLM engineers on implementation and deployment Requirements Currently pursuing MS/PhD in Computer Science, Machine Learning, Natural Language Processing, or related fields Publications at top-tier venues (ICML, NeurIPS, ICLR, ACL, EMNLP, NAACL) Strong programming skills in Python and PyTorch Ability to work in-person at our San Francisco office Ability to work independently and collaborate across research and engineering teams Preferred Experience with self-evolving agent systems Proficiency in CUDA programming and custom kernel development for LLM operations Background in reinforcement learning-based LLM fine-tuning Track record of contributions to production inference systems such as vLLM, TensorRT-LLM, SGLang, or Hugging Face ecosystem Experience bridging academic research with production systems Open-source contributions to widely-used ML infrastructure projects

(REQ ID: 2501)

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