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.
走进这场面试
免费 · 一场按这个岗位校准的真语音模拟
可能的面试形态
Google's standard loop typically includes coding rounds, a googleyness/behavioral round, and for research-adjacent roles may include an ML/system design discussion
这场面试考什么
- 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
常见提问方向
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
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