Staff Software Engineer, Data Pipelines, DeepMind

Socket.dev; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Google DeepMind is recruiting a Software Engineer to own the Gemini interface and power the AI-driven user experience. You will build pipelines, test problems, and visualize results across 2D/3D simulations, improving agent performance and benchmarking.

You will collaborate with ML researchers and engineers, lead a fast-paced team, and help translate product goals into scalable technical solutions that advance AI capabilities for billions of users.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of software development experience.
• 5 years of testing and launching software products.
• 5 years of coding with Python, C/C++, TensorFlow, Java, Kotlin, SQL.
• 3 years of software design and architecture.
• Experience with Flume, data processing pipelines, SQL.
• Master’s degree or PhD in Engineering/CS (preferred).
• 8 years of data structures & algorithms (preferred).
• 3 years in technical leadership roles (preferred).
• Experience with compilers, GPU programming, ML architecture, performance optimization, benchmarking, runtimes, ML algorithms (preferred).

Responsibilities

• Be the key owner of the interface powering the Gemini machine learning models responses and user presentation.
• Build robust pipelines and jobs powering critical investments across Google.
• Collaborate with UX, PM, and cross-functional partners; guide GeminiApp into an AI-driven architecture.
• Direct day-to-day execution of a high-tempo engineering team; unblock complex challenges; ensure timely launches.
• Serve as a technical partner for Product, UX, and Backend teams; influence server-side infra and translate goals into tech strategies.

Skills

Software development

Testing & launching software products

Coding: Python, C/C++, TensorFlow,Java

Software design & architecture

Data processing pipelines

Education

Bachelor’s degree or equivalent practical experience

Master’s degree or PhD in Engineering/CS

Tools

Flume

TensorFlow

SQL

Python

C/C++

Java

Kotlin

Job description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products.
• 5 years of experience with coding (e.g., Python, C/C++, TensorFlow, Java, Kotlin, SQL).
• 3 years of experience with software design and architecture.
• Experience with Flume, data processing pipelines, SQL.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• Experience with any of the following: compilers, GPU programming, Machine Learning architecture, performance optimization, benchmarking, runtimes, Machine Learning algorithms.

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.

Artificial intelligence could be one of humanity’s most impactful inventions. At Google DeepMind, our team of scientists, engineers, and machine learning experts works together to advance the in the field. We leverage our technology for broad public benefit and scientific discovery, collaborating on critical challenges while prioritizing safety and ethics above all else.

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 diverse 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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

• Be the key owner of the interface powering the Gemini machine learning models responses and how it is presented to the user.
• Build bullet proof pipelines and jobs that power one of the most critical investements across Google.
• Collaborate closely with UX, Product Management (PM), and other cross-functional partners, serve as a thought leader in the evolution of GeminiApp into a natively AI-driven application, effectively bridging the gap between imaginative goals and technical feasibility.
• Direct the day-to-day execution of a high-tempo engineering team, unblocking complex technical challenges and ensuring the timely launch of performant, high-quality features.
• Serve as a technical partner for Product, UX, and Backend teams, influencing server-side infrastructure and translating ambiguous product goals into actionable technical strategies.