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. To learn more, visit www.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.

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 looking for an exceptional

Middle / Senior Machine Learning Engineer / Data Scientist





to join our growing AI team. In this role, you will design, build, deploy, and improve ML/LLM-powered services and features that power intelligent automation and AI-driven product experiences across the Workato platform. You will work closely with our Engineering, Product, and Design teams to define and track product metrics and evaluation strategies, design customer-facing experiments and dive deep to provide actionable insights.This role is adecuado for someone who combines strong ML/LLM intuition, software engineering skills and a practical mindset for shipping reliable, scalable AI systems.

In this role, you will also be responsible to:

Build and improve AI services

using LLMs and custom machine learning models for production use cases.

Design, develop, and operate ML/LLM systems

end-to-end, from prototyping to deployment and monitoring.

Write high-quality Python code

that is testable, maintainable, and efficient.

Improve validation, observability, and performance monitoring

for ML services (quality, latency, reliability, cost).

Partner cross-functionally

with product managers, platform engineers, and other stakeholders to ship AI-powered product capabilities.





Evaluate and improve existing implementations

by identifying bottlenecks, bugs, and opportunities for optimization.

Design controlled experiments

to test the features for our AI-based products and perform deep analysis from the results to find actionable insights

Contribute to technical design and code reviews , helping raise engineering quality across the team.

Experiment and iterate

on model behavior, prompting, retrieval, tool use, or orchestration strategies to improve user outcomes.

Requirements Qualifications / Experience / Technical Skills

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or equivalent practical experience

3+ years

of experience in

Machine Learning Engineering, Data Science , or a similar role.

Strong

Python

programming skills.

Hands-on experience with

NLP and/or LLM-based systems .

Strong understanding of

software engineering fundamentals

(testing, code quality, debugging, version control).

Ability to work collaboratively in a fast-moving environment and drive projects with ownership.

Nice to Haves

Experience with tool-use agents or workflow-aware AI systems.

Experience building AI products in enterprise SaaS environments.

Experience with A/B testing and statistical significance techniques.

Experience with LLMOps/MLOps tooling and practices (monitoring, evaluation pipelines, model rollout, CI/CD).

Experience working with modern data warehouses such as Amazon Redshift Snowflake.

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📌 Senior Data Scientist (Madrid)
🏢 Workato
📍 Madrid