1 day ago
Bengaluru, IndiaStaff+
Responsibilities
- Build, test, ship, and performance-tune 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 data 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 outcomes.
- Work directly in customer environments and provide field feedback that informs Google Cloud’s 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 ecosystem products, technologies, or languages including 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, enterprise LLM applications, Gemini, agents, RAG, vector search, LLM-native metrics, state management, and granular tracing.
- Preferred experience migrating analytics, Spark, or database workloads between platforms with measured cost or performance results.
Benefits
- Google Cloud provides access to its AI portfolio, including Gemini models and the Vertex AI platform, with collaboration opportunities involving DeepMind engineering and research teams.
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.