Senior Software Engineer, Generative AI, Core
@ Google

Sunnyvale, CA
$200,000
On Site
Full Time
Posted 22 hours ago

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Job Details

About the Role

As a Senior Software Engineer, Generative AI, Core at Google, you will work at the intersection of innovative research and cutting edge engineering. You will collaborate with DeepMind researchers and partner with Alphabet's internal teams to bring generative models into real-world applications.

Minimum Qualifications

Bachelor’s degree or equivalent practical experience and at least 5 years of experience training and deploying generative models with a focus on real-world applications. Proven experience in handling large datasets, including data cleaning, pre-processing, and analysis.

Preferred Qualifications

Master's or PhD in Computer Science or a related field along with 5 years of experience with data structures and algorithms. Experience contributing to open-source projects, academic publications, and research work combined with familiarity with Gemini models or machine learning frameworks. Understanding of deep learning architectures (e.g., Transformers) and deployment on Alphabet infrastructure (especially TPUs) is essential. Excellent communication, collaboration, and problem-solving skills are required.

Responsibilities

  • Collaborate with DeepMind researchers to train cutting-edge generative models.
  • Integrate models into workflows with Alphabet's internal teams.
  • Curate and refine pre-training, instruction tuning, and evaluation processes.
  • Analyze model outputs and user feedback to enhance performance.
  • Apply large language model post-training techniques for code generation and bug-fixing workflows.

Key Skills/Competency

  • Generative AI
  • Machine Learning
  • Deep Learning
  • Transformers
  • Data Analysis
  • Software Engineering
  • Research
  • TPU Deployment
  • Distributed Systems
  • Collaboration

How to Get Hired at Google

🎯 Tips for Getting Hired

  • Tailor your resume: Highlight generative AI and deep learning skills.
  • Showcase projects: Include relevant open-source and research work.
  • Prepare interviews: Review technical questions on algorithms and ML frameworks.
  • Network with Googlers: Connect on LinkedIn and attend tech meetups.

📝 Interview Preparation Advice

Technical Preparation

Review deep learning frameworks and libraries.
Practice coding algorithms and system design.
Study TPU deployment and model optimization.
Analyze case studies of generative models.

Behavioral Questions

Describe a challenging project and resolution.
Explain collaboration experiences in technical teams.
Discuss handling tight deadlines under pressure.
Share experiences in adapting to change.

Frequently Asked Questions