Senior AI Research Scientist

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 Workatos 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

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. Thats 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

We are looking for an exceptional AI Research Scientistto join our growing this role you will be responsible to:

• Explore workflowaware planning costoptimised RAG tooluse evaluation and multiagent collaboration.

• Prototype and benchmark models; present findings internally and externally.

• Collaborate with Product & Engineering to ship researchbacked features.

• Contribute to opensource repos and author technical blogs.

Requirements

• MS/PhD in Computer Science ML or related fieldor equivalent experience.

• Handson with PyTorch/JAX and modern LLM frameworks.

• Strong publication record in top-tier ML venues (NeurIPS ICML ICLR) or demonstrable impactful experimental work; handson experience with largescale model training transformer architectures reinforcementlearning techniques and CUDA.

• Curiositydriven and selfdirected.

• Ability to explain complex ideas to nonexperts.

• Team player who welcomes feedback and knowledgesharing.