AI-Powered UX Engineer

WeAreTechWomen; United States; On-site; USD 180,000 - 250,000; Full time

Job summary

Google DeepMind seeks a Software Engineer to advance AI-driven user experiences. You will design full-stack systems for research-driven products, prototype solutions, and visualize results across 2D/3D environments.

The role emphasizes AI-enabled UX, rapid prototyping, and cross-disciplinary collaboration within a mission-driven team. You will collaborate with ML researchers, UX designers, PMs, and engineers to ship scalable features, optimize performance, and build robust AI pipelines.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of coding experience in C, C++, Java, or Python.
• 5 years of experience with front- and back-end technologies and modern web libraries/frameworks (Angular, Svelte, React).
• Experience building prototypes for AI/ML systems and AI-native tool-chains.
• Experience with AI technologies and UI prototyping.

Responsibilities

• Design and develop the front- and back-ends of user-facing products.
• Design, develop, test, and iterate on stable but experimental code for new user-facing features.
• Build dynamic workflows and collaborative tools tailored to user needs and content types.
• Take ownership of engineering implementation, delivery, bugs and performance.
• Engage in prompt engineering to create AI-driven user experiences.

Skills

AI/ML prototypes

Frontend/Backend web

Programming languages

UI prototyping

Prompt engineering

Education

Bachelor’s degree or equivalent

Master’s or PhD in engineering/CS

Job description

Google DeepMind seeks a Software Engineer to advance AI-driven user experiences. You will design full-stack systems for research-driven products, prototype solutions, and visualize results across 2D/3D environments.

The role emphasizes AI-enabled UX, rapid prototyping, and cross-disciplinary collaboration within a mission-driven team. You will collaborate with ML researchers, UX designers, PMs, and engineers to ship scalable features, optimize performance, and build robust AI pipelines.