Mid
Software Engineer at Google DeepMind prototyping GenAI pipelines and infrastructure
This Mountain View-based role sits within Google DeepMind, applying research to high-impact problems: prototyping GenAI solutions, curating datasets, and building ML pipelines for generative media, multimodal understanding, and reinforcement learning. Candidates should expect coding, systems-thinking, and ML-lifecycle questions grounded in production-quality engineering (testing, debugging, deployment).
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What this interview tests
- Taking ML/research prototypes from proof-of-concept to production
- Core coding: data structures, algorithms, Java/C/C++/Python/Go
- Systems-level problem analysis and debugging
- Testing rigor (integration, performance, security)
- Data curation for ML pipelines
Common question themes
Design or extend an ML data pipeline for a generative or multimodal use case
Coding problem involving data structures and algorithms
Debug a complex production system issue and find root cause
Describe managing a project from proof-of-concept through to implementation
How you approach code review and testability for a shared codebase
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