Ship GenAI research into production ML pipelines at Google DeepMind

This Google DeepMind Software Engineer role (Sunnyvale, hybrid) sits at the boundary of research and production: prototyping GenAI solutions for generative media and multimodal understanding, building ML pipelines, and hardening product code with integration/performance/security testing. It requires 2 years of experience training generative AI models for media generation, building models in TensorFlow/PyTorch/JAX, managing ML infrastructure (deployment, evaluation, optimization, data processing), and general software development in Java/C/C++/Python/Go. Expect the mock to blend ML system design with core coding fundamentals (data structures/algorithms) and production-engineering rigor.

Step into this interview

Free · a live voice mock calibrated to this exact role

Practice this interview

What this interview tests

Training and evaluating generative AI models for media generation
ML framework tradeoffs (TensorFlow, PyTorch, JAX)
ML infrastructure: deployment, evaluation, optimization, data pipelines
Core data structures and algorithms
Debugging and root-causing production system issues (performance, security, reliability)