Senior Software Engineer, Launch Intelligence, DeepMind

Google • Mountain View, CA

10d

About The Position

At Google DeepMind our mission is to build the world's first general-purpose learning agent. Central to this mission is the complex task of measuring the intelligence of our prototypes. As a Software Engineer, you will be working with the cutting edge AI agents developed by our exceptional team of Machine Learning and Neuroscience research scientists. Your responsibilities will include everything from creating systems for agent testing using 2D and 3D games to developing test problems within physics simulators. You will create graphical visualization of results, build competitive agent leaderboards and test new algorithms on robots. To succeed in this role you will need to have a strong foundation in software engineering and enjoy working on a wide range of challenging problems within a mission-driven team. Artificial intelligence will be one 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 diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

Requirements

• Bachelor’s degree in Computer Science, Artificial Intelligence, a related technical field or equivalent practical experience.
• 5 years of experience with core software engineering and building reliable, high-traffic production systems.
• Experience with relevant machine learning (ML) frameworks such as JAX, TensorFlow, or PyTorch, including for inference and serving.
• Excellent programming skills in Python and C++.

Nice To Haves

• Experience in full-stack engineering, and working with front-end frameworks (e.g., React, Flutter, or simple web UIs) to visualize ideas, as well as back-end services to power them.
• Experience in delivering features that leverage AI (e.g., LLMs, multimodal models) to a large user base.
• Experience in prompt engineering, and understanding of evaluation strategies, pre-training, and post-training concepts.
• Familiarity with multimodal data and processing pipelines (e.g., video/audio/text).
• Ability to lead zero-to-one development by transforming raw ideas into rapid prototypes and leveraging full-stack experience to drive projects through to full production.

Responsibilities

• Work directly with engineering, product, and research teams in Google DeepMind to quickly ideate, build, and iterate on proof-of-concept integrations that leverage artificial intelligence (AI) capabilities.
• Validate new ideas, utilizing the latest advancements in multimodal Large Language Models (e.g., audio/text) to build functional, tangible prototypes.
• Be a flexible, full-stack thinker, capable of jumping between different parts of the stack, from hacking together agent harness for Gemini to quickly bringing up an application demo for proving out product experiences.
• Apply your broad engineering expertise to create the initial sparks that could eventually impact users globally.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level