Intern, AI Engineering

Навыки

• AI-агенты
• CUDA / ONNX / TensorRT
• Дообучение моделей
• LLM
• Инференс LLM
• Machine Learning
• NLP

О компании и продукте

• Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
• 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!

Задачи

• 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
• We are now filling intern positions for Winter 2026 and Spring 2027
• Research Areas
• LLM Agent Systems : Design and implement intelligent agent architectures for complex enterprise automation tasks, including multi-agent collaboration, MCP, and reasoning frameworks
• Efficient LLM Fine-tuning : Develop novel methods for parameter-efficient adaptation, alignment, and reinforcement learning for large language models
• High-Performance LLM Inference : Optimize inference pipelines through systems-level innovations, kernel development, and deployment strategies
• 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

Требования

• Qualifications / Experience / Technical Skills
• 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: 2690)

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