Google layoffs: Everything developers need to know

Google’s recent layoffs reshaped its tech teams, signaling a clear focus on AI, cloud infrastructure, and automation.

For developers globally, these layoffs are more than buzzwords: they’re a reality check for what takes to get hired—and thrive—at Google in its AI-driven evolution.

So what does this mean for developers who want to land a role at Google?

In this blog, we'll answer that question by exploring: 

• A timeline of Google’s layoffs and the strategic decisions behind them.

• Key insights into Google’s priorities and what they mean for developers.

• How to stay competitive by upgrading your skills and resume.

• A tech layoff survival kit to navigate job hunting effectively

Let's dive in.

The Google layoff timeline#

Google’s layoffs aren’t just about lowering costs—they’re about reshaping the company for the AI-driven future it’s betting on. Here’s what’s driving the change:

The Google workforce facing cuts and restructuring signifies a change in strategy to allocate more funds toward AI infrastructure. Here’s a breakdown of key events: 

Google layoffs 2023#

• After cutting down on approximately 6% of its workforce, Google lost $2.1 billion. The company maintained that these layoffs were necessary to fund its evolving strategic goals.

Key takeaway: No tech giant is immune to strategic changes. For developers, adaptability and staying aligned with industry trends are crucial.

Google layoffs 2024#

• Cuts to Google Assistant teams followed the implementation of generative AI features like Google Bard.

• Employees in Python, Flutter, and Dart teams were let go as part of efforts to simplify internal structures and refocus resources.

• Key technical infrastructure teams were reorganized and relocated to Germany, India, and Mexico.

• The Python team’s move to Munich highlights Google’s focus on balancing cost efficiency with the continued relevance of Python in AI and machine learning projects.

Key takeaway: AI is changing the nature of engineering roles. Teams tied to lower-priority projects face cuts, while AI-related roles will become more essential and in demand.

What do Google layoffs mean for developers?#

Google is laser-focused on AI, automation, and cloud computing. Developers who align with these priorities will have the best shot at future-proof careers—not just at Google but across the wider tech industry, which also has its eye focused on these technologies.

Behind Google’s layoffs lies a roadmap for developers. Here’s a quick breakdown of what some other key Google decisions indicate about its trajectory:

1. Google shifts core teams to global tech hubs
   Reason: To reduce costs and access a larger tech talent pool in high-growth areas like India, Brazil, Ireland, and Germany.
   

2. Layoffs occur in software and legacy teams
   Reason: Overhiring during the pandemic created too-large teams, so Google downsized to limit bureaucracy and prioritize technologies like AI and machine learning.
   

3. Google makes major $100B AI investment
   Reason: Google’s AI revenue surged with a profit increase of 60% in 2024’s first quarter, indicating that Google’s AI focus is paying off and that it’s likely to stay there.
   

Tech layoffs survival kit: Google edition#

With a $100 billion investment in AI, Google is betting big on an AI-driven future. Developers who align their skills with this vision will be poised to lead the next wave of innovation at the company.

Here’s where to start.

Upgrade core AI and ML skills#

Boosting your AI skills will help set you apart in Google’s candidate pool. Here’s what to do:

Refresh AI basics#

• Core foundations: 

  • Math and CS fundamentals: Algorithms, data structures, and statistics
    

• Languages to know: 

  • Go: Used in apps like Google Cloud microservices, Maps, Gmail, etc. 

  • Python: Used to build AI in Google Home, Google Assistant, Google Advertisement, etc. 

  • Java: Google Suite is built in Java and is part of other Google codebases. 

  • Rust: Leading coding language for Google developers in performance and security, and is a memory-safe language.
    

• Popular machine learning frameworks:

  • Libraries: TensorFlow, PyTorch, scikit-learn, Matplotlib

  • Models to learn: Linear regression, decision trees, KNN, and K-means

  • Evaluation metrics: Precision, recall, F1-score, and cross-validation

  • Advanced models: Google’s LaMDA, BERT, and Gemini for NLP and deep learning expertise
    

Dig deep in generative AI #

Google’s investments in AI and ML go back decades. In 2023, Google’s LLM model, LaMDA, created the blueprint for other generative AI systems. 

Google’s next developers who can contribute to its next-generation AI projects include: 

• Jarvis: Experimental AI assistant powered by Gemini 2.0

• SGE (Search Generative Experience): Google’s AI-powered search upgrade

• Project Astra: A multimodal AI assistant using text, images, and audio inputs

Google also has a robust proprietary AI tech stack that developers should know about. Familiarize yourself with Google tools like Vertex AI, Cloud Vision, speech-to-text APIs, and Tensor Processing Units (TPUs).

Learn prompt engineering#

Prompt engineering helps developers design inputs for its models: 

• Google Gemini: Prompt engineering is essential for working with LLMs like Google Gemini. It involves creating inputs that guide AI’s responses, which is key to building the smart AI-powered tools Google wants and needs. 

• Use of Google LLMs: Google considers prompt engineering vital for effectively operating advanced LLMs like BERT, PaLM, and Bard. 

You’ll stand out if you can learn to:

• Design optimized prompts: Use Prompt Poet to create task-specific inputs.

• Use frameworks: Explore LangChain and Hugging Face for prompt-based AI projects.

• Build projects: Develop chatbots, virtual assistants, or personalized AI-powered tools.
  

Explore Google Cloud#

There is an increasing demand for cloud skills, and Google Cloud provides various relevant services, including Google Cloud Platform (GCP).

• GCP has tools and serverless options for developers, like Cloud Functions and Cloud Run. 

Get started with Google BERT#

Learning Google BERT (Bidirectional Encoder Representation from Transformers) is a must-have skill; besides being a Google product, it is an important building block for ML and AI development at Google, especially when working with natural language processing (NLP). 

To add these skills to your developer toolkit, here’s what you can do:

• Take courses and tutorials: Take Google’s ML courses, Coursera, or Kaggle.

• Build personal projects: Create chatbots, AI-powered tools, or custom ML models using TensorFlow or PyTorch.

• Show off your skills: Showcase AI-driven projects on GitHub and LinkedIn.

• Learn more: Explore Transformer architecture and newer generative models like Llama.

Shine in interview loops with the right prep#

Google’s technical interviews are difficult because the company expects more from its employees than technical expertise. Google CEO Sundar Pichai defines a superstar programmer as someone hungry for learning and growth. 

Here's a detailed rundown of what you can do to embody these qualities, prepare for your interview loop, and stand out.

Understand the interview process#

Expect multiple stages, including:

• Application review: Highlight impact-driven projects and leadership roles.

• Online assessments: Practice on LeetCode, HackerRank, or Educative.

• Phone/on-site interviews: Prepare for System Design and deep technical discussions.

Fine-tune core technical skills#

Google’s technical interviews are notoriously challenging, so be prepared to speak to these essentials (even if it's been a while since you studied or used them):

• Data structures and algorithms: Master sorting, searching, graphs, and dynamic programming.

• Coding efficiency: Practice writing clean, optimized code while explaining your thought process.

You'll want to boost your System Design skills, too.

Google products serve billions of users daily, so engineers must design fault-tolerant, scalable systems that won’t crash under very heavy traffic. Make sure to add advanced System Design principles to your prep.

Other ways to grow your System Design skills include:

• Study System Design architectures of tech giants like Facebook, Netflix, Google, etc., through case studies. 

• Practice System Design problems on platforms like LeetCode or Educative.

• Build scalable personal projects like URL shorteners, chat apps, or dashboards.

Sharpen your soft skills#

At Google, “Googleyness” goes beyond technical ability—it’s about how you approach challenges, work with others, and adapt to the unknown. Here’s how to showcase it:

• Thrive in ambiguity: How you push forward, adapt, and conquer in the presence of uncertainty at the workplace. Mention times you took the initiative despite the risk.  

• Own the good and the bad: Times when you took charge of challenging projects and succeeded, but also times you fell flat and how you handled it. 

• Teamwork, with no strings attached: Google values collaboration and transparency; highlight experiences where you maintained a culture of honest communication and trust to achieve individual and collective goals.

Build a strong, relevant portfolio#

Your resume doesn’t mean much without a strong portfolio of work to back it up.

Adding real-world projects highlighting AI, machine learning, data science, and software development skills can help you make a good impression on Google recruiters.

Here’s how to build a portfolio designed to impress Google interviewers:

Choose projects that matter:#

• Focus on projects related to the roles you want and are impact-driven.

• Highlight your skills that align with it—like the right programming languages, frameworks, or technologies.

Get hands-on experience:#

• Follow Google coding interview guides and project courses to build practical skills.

• Build projects with current tech stacks and industry tools like TensorFlow, PyTorch, Docker, and Google APIs.

Share your knowledge:#

• Contribute to open-source projects (or lead your own!).

• Share your work on GitHub, LinkedIn, or a personal portfolio site.

Google layoffs 2025: More may come#

Despite Google’s massive AI investments, CEO Sundar Pichai warned at the New York Times DealBook Summit that generative AI breakthroughs will become more difficult in 2025, with financial returns requiring a steep climb. However, he has also predicted that AI progress will become more accessible to millions in the coming years.

At a recent Google all-hands meeting, Pichai stressed the need for smart tradeoffs when managing headcount—hinting that more layoffs may be on the horizon as Google prioritizes efficiency.

With this in mind, it's even more important than you align your skills to Google's vision so that you become as indispensable as possible.

Take the next step in your career#

Based on Google’s business bet on AI, the next wave of tech jobs will likely belong to developers who can adapt to its AI-driven focus.

In our current tech climate, layoffs are a stark reminder of the importance of continuous learning and strategic career planning. Stay ahead by equipping yourself with the right tools and building job-ready skills in AI, automation, and cloud technologies.

The future of tech belongs to those who build it. Stay competitive, adapt fast, and start building the AI-driven systems companies need now. 

If you need more support, use resources like our Tech Layoff Survival Guide, which provides a step-by-step roadmap to staying competitive and returning to the game.