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Follow Alex — a Stanford CS senior applying to Google Brain — through every step. Click to explore the full flow.

A
Alex Johnson · Stanford University · Computer Science
Step 1

Tell us about the job

Alex found this ML Engineer role at Google. She pastes the job description and Provieo extracts exactly what matters.

job-description.txt
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Machine Learning Engineer, New Grad
Google · Google Brain · Mountain View, CA (Hybrid)
About the role
Google Brain builds the AI systems that power Search, Translate, Photos, and hundreds of products used by billions of people. As a Machine Learning Engineer you'll work directly on research-to-production pipelines.

What you'll do:
• Design and train large-scale ML models using TensorFlow and JAX
• Build efficient data pipelines on Google's infrastructure (TPUs, BigQuery)
• Collaborate with research scientists to productionise novel architectures
• Contribute to open-source ML tooling (TensorFlow, TFX, TFLite)
• Evaluate model quality and drive A/B experiments at Google scale

Minimum qualifications:
• B.S./M.S. Computer Science or equivalent practical experience
• Strong Python — TensorFlow, PyTorch, or JAX
• Experience training and evaluating ML models end-to-end
• Solid understanding of linear algebra, probability, and optimization

Preferred qualifications:
• Research publications or open-source contributions in ML
• Experience with TPU/GPU training at scale
• Knowledge of NLP, computer vision, or recommendation systems
• Internship experience at a top AI lab or tech company