1 day ago
Tokyo, JapanStaff+
Responsibilities
- Build and ship production data and machine learning workloads with customers using PySpark, SQL, Python, BigQuery, Managed Spark, Spanner, and AlloyDB.
- Present working proofs using customer data, including de-identification of sensitive information such as PCI and PHI.
- Build lakehouse architectures, metadata, semantic context, and access controls for agentic solutions.
- Train, evaluate, deploy, and monitor machine learning and agentic components against customer business metrics.
- Refactor and migrate analytics, Spark, and operational database workloads to Google Cloud with measured price-performance results.
- Work directly in customer environments and provide field feedback that informs the Google Cloud product roadmap.
Requirements
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- At least 2 years of experience in software engineering, data engineering, solution architecture, machine learning, or technical consulting, including coding in Python and SQL.
- Experience with data cloud products and technologies such as Apache Spark, PySpark, BigQuery, Spanner, Data Catalog, and AlloyDB.
- Experience taking production-grade data cloud solutions from conception to launch, architecting cloud data systems, and building structured and unstructured pipelines.
- Experience training, evaluating, and deploying machine learning models in production.
- Preferred experience implementing multi-agent systems with LangGraph, CrewAI, or ADK and patterns such as ReAct, self-reflection, and hierarchical delegation.
- Preferred experience with prompt development, model evaluation, LLM applications over enterprise data, Gemini, agents, RAG, vector search, workload migration, and LLM-native metrics.
Benefits
- Work arrangement involves embedding directly with strategic customer accounts in Google Cloud’s Go-To-Market team.
- Access to Google’s AI portfolio, including Gemini models and the Vertex AI platform.
- Collaborate with DeepMind engineering and research teams and contribute field insights to product development.
Tech Stack
Categories
Forward Deployed
About Google
Google builds consumer and enterprise software and services including Search, Android, YouTube, Chrome, Maps, Gmail, and Google Cloud. Its business model centers on digital advertising and paid cloud, software, and hardware offerings (e.g., Pixel and Nest) for consumers, developers, and organizations. Founded in 1998 and headquartered in Mountain View, California, Google operates globally as a subsidiary of Alphabet Inc.