
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in San Francisco, United States"), this listing's salary midpoint is about 92% lower. The offer sits below the benchmark range (€8,681–€13,311). Range-width comparison is limited because one of the salary bands is incomplete. This benchmark is based on 2 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| All roles in San Francisco, United States | €8,681/per month | €10,996/per month | €13,311/per month |
| Pay in our data — not quoted in ad (Senior) | €916/per month | €916/per month | €916/per month |
About Workato 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. 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. Responsibilities We are looking for an exceptional AI Research Scientist to join our growing team. In this role, you will be responsible to: - Explore workflow‑aware planning, cost‑optimised RAG, tool‑use evaluation, and multi‑agent collaboration. - Prototype and benchmark models; present findings internally and externally. - Collaborate with Product & Engineering to ship research‑backed features. - Contribute to open‑source repos and author technical blogs. Requirements Qualifications / Experience / Technical Skills - MS/PhD in Computer Science, ML, or related field—or equivalent experience. - Hands‑on with PyTorch/JAX and modern LLM frameworks. - Strong publication record in top-tier ML venues (NeurIPS, ICML, ICLR) or demonstrable impactful experimental work; hands‑on experience with large‑scale model training, transformer architectures, reinforcement‑learning techniques, and CUDA. Soft Skills / Personal Characteristics - Curiosity‑driven and self‑directed. - Ability to explain complex ideas to non‑experts. - Team player who welcomes feedback and knowledge‑sharing.
Job Details
Responsibilities
- Explore workflow-aware planning, cost-optimised RAG, tool-use evaluation, and multi-agent collaboration
- Prototype and benchmark models; present findings internally and externally
- Collaborate with Product & Engineering to ship research-backed features
- Contribute to open-source repos and author technical blogs
Requirements
- MS/PhD in Computer Science, ML, or related field, or equivalent experience
- Hands-on experience with PyTorch/JAX and modern LLM frameworks
- Strong publication record in top-tier ML venues (NeurIPS, ICML, ICLR) or impactful experimental work
- Experience with large-scale model training, transformer architectures, reinforcement-learning techniques, and CUDA
- Curiosity-driven and self-directed
- Ability to explain complex ideas to non-experts
- Team player who welcomes feedback and knowledge-sharing
Skills & Technologies
Education Level
MastersBenefits & Perks

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