AI Innovation Engineer, Google Cloud

Machine Learning Engineer

Location options: Frankfurt am Main, Germany; Munich, Germany; London, UK.

Minimum Qualifications

• Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
• 6 years of experience in software or data engineering.
• Experience solving real‑world problems using machine learning methodologies (deep learning, reinforced learning), model identification, selection and AI operations such as model monitoring.
• Experience solving real‑world problems using Generative AI and agentic orchestration frameworks (e.g., LangChain, CrewAI, or Vertex AI Agent Builder) and vector databases.
• Experience with one of the following programming languages: Python, Go, or Java.
• Experience with design patterns, testing frameworks, and API contract design.

Preferred Qualifications

• Experience in financial services, including regulatory and operational aspects of clearing, settlement, or custody.
• Familiarity with FSI regulatory practices, data residency, encryption at rest/transit (CMEK), and explainable AI requirements in banking.
• Experience with data modeling of relational, NoSQL, and analytical data (Star Schema, Data Vault, etc.).
• Experience working in a high‑maturity DevOps culture (trunk‑based development, automated testing, blue/green deployments).
• Experience with BigQuery, Vertex AI, Dataflow, and Pub/Sub, and ability to move from a vague business problem to a structured PRD and working technical demo.

Responsibilities

• Collaborate with clients to transform initial concepts into reality, creating solutions using the latest machine learning and Generative AI technologies.
• Identify high‑impact AI use cases in the capital markets finance industry, particularly within high‑stakes clearing, settlement, and custody environments.
• Build autonomous agentic workflows utilizing machine learning and Generative AI technologies for fully autonomous or human‑in‑the‑loop scenarios.
• Translate client requirements into Product Requirement Documents (PRDs), defining critical user journeys and success metrics.
• Evaluate and integrate AI solutions with modern data foundations, including relational databases, data lake houses, and real‑time streaming architectures.
• Ensure prototypes are built with a production‑first mindset, implementing basic CI/CD pipelines and Infrastructure‑as‑Code (e.g., Terraform) for reproducible and secure environments.
• Create clear technical guides to facilitate seamless hand‑off from proof‑of‑concept to engineering teams.

Benefits

• Individual pay determined by skills, experience, and education.
• Germany: €124,000 - €128,000 (EUR) + 15% bonus target + equity + benefits.