At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining,
natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer various learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $253000 (USD) + 15% bonus target + equity + benefits
Learn more about
benefits at Google.
Responsibilities
- Select and maintain a "gold standard" set of robot hardware, benchmark the model’s zero-shot performance on these platforms to understand capabilities and limitations before they reach partners.
- Build a library of out-of-the-box demo tasks (e.g., visual navigation, pick-and-place, semantic reasoning) that showcase the model's power in real-world scenarios.
- Serve as the primary technical point-of-contact for trusted testers (TT), troubleshoot unique hardware-software integration issues and feed those insights back into the core research team.
- Travel to partner sites up to 25% of the time.
Minimum qualifications:
- Bachelor’s degree in Computer Science, Robotics, or equivalent practical experience.
- 5 years of experience in software development, AI engineering, or solutions architecture.
- Experience with machine learning tools and algorithms, specifically Large Language Model (LLMs)/Vision Language Models (VLMs) and deep learning.
Preferred qualifications:
- Experience with (robot operating system) ROS/ROS2, simulation environments (Isaac Sim, MuJoCo), or on-device deployment (Jetson, TPU).