Senior Research Engineer, Gemini Omni, DeepMind

Socket.dev; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google DeepMind seeks a Software Engineer to join our team working on cutting-edge AI agents and multimodal models. You will help translate research into production systems, build test problems, and create visualization of results for agent leaderboards.

You will work with ML scientists and engineers across domains to advance Gemini Omni capabilities. We value strong software engineering foundations and the ability to tackle diverse, mission-driven challenges while delivering high-quality AI

Qualifications

• Minimum: bachelor’s degree or equivalent practical experience.
• 3 years testing, maintaining, or launching software products, and 1 year in software design/architecture.
• 3 years experience with ML algorithms, research methodologies, and language modeling.

Responsibilities

• Translate research into production-ready systems spanning rapid prototyping to deployment.
• Architect and advance multimodal foundation models for Gemini Omni capabilities.
• Design, train, and scale architectures using RL/RLHF/RLAIF to improve reasoning and generation quality.
• Optimize models and inference pipelines for low-latency, cost-effective serving at scale.
• Collaborate with research scientists, product managers, and infra teams to deliver AI features to billions of users.

Skills

Software testing/maintenance/launch

Software architecture

ML algorithms

Research methodologies

Language Modeling

Education

Bachelor’s degree or equivalent practical experience

Tools

JAX

PyTorch

TensorFlow

Job description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience in development with JAX, PyTorch, or TensorFlow.
• 3 years of experience with Machine Learning algorithms, research methodologies, and Language Modeling.

Preferred qualifications:

• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.

About the job:

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.

We research and develop machine learning models for billions of Google users.

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 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 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

• Translate research into production-ready systems, driving the full lifecycle from rapid prototyping and large-scale dataset curation to model training, evaluation, and real-world deployment.
• Architect and advance multimodal foundation models spanning generative media (text, image, audio, and video) and rich cross-modal understanding to power next-generation Gemini Omni capabilities.
• Design, train, and scale advanced architectures leveraging techniques such as reinforcement learning (RL/RLHF /RLAIF) to enhance reasoning, steerability, and multimodal generation quality.
• Optimize model architectures and inference pipelines using quantization, distillation, pruning, and kernel optimization to achieve low-latency, cost-effective serving at scale.
• Partner cross-functionally with research scientists, product managers, and infrastructure teams to identify emerging technical opportunities and bring novel AI features to millions of users.