Associate
Software Engineer applying ML/GenAI research at Google DeepMind, 2 years of applied experience required
An entry-to-mid Software Engineer role at Google DeepMind requiring 2 years of experience developing ML models (TensorFlow, PyTorch, or JAX) and applying ML/statistics/diffusion model theory in applied research, alongside general software development in Java, C, C++, Python, or Go. The role spans prototyping GenAI features, building ML pipelines for generative media and multimodal understanding, and owning code quality, testing, and deployment lifecycle.
Step into this interview
Free · a live voice mock calibrated to this exact role
Likely format
Google's standard loop typically includes coding rounds, a googleyness/behavioral round, and for research-adjacent roles may include an ML/system design discussion
What this interview tests
- Applied ML model development (TensorFlow/PyTorch/JAX)
- GenAI pipeline building for generative media and multimodal tasks
- Software engineering rigor: testing, code review, security
- Root-cause debugging of complex system issues
- Technical documentation and technical debt management
Common question themes
Describe an ML pipeline you built for a generative or multimodal task, from data to evaluation
Where has applied ML/statistics or diffusion model theory actually changed a technical decision you made
Tell me about a bug or system issue you debugged that required root-causing across hardware, network, or service layers
How do you approach code review and testing (integration, performance, security) on a project you own
How do you decide when to pay down technical debt versus ship the next feature
Related interviews
Senior
Software Engineer, Serverless Networking, Infrastructure
Staff
Staff Software Engineer, Mobile (Android), YouTube
Mid
Software Engineer
Cloudflare
Mid
Machine Learning Engineer
Coinbase
Senior
Senior Software Engineer - Data Platform
Roblox
Senior