Google's Education team is pioneering high-impact, society-benefiting educational experiences using Generative AI. They are looking for engineers to build novel solutions from pronunciation practice tools to rich learning journeys that will reach learners and educators globally via key Google surfaces.
Requirements
- 5 years of experience with software development in one or more general-purpose programming languages, such as Python.
- 3 years of experience in the design, development, testing, and maintenance of scalable software or ML systems.
- 3 years of experience with specialized Machine Learning areas, such as Natural Language Processing (NLP), speech/audio processing, or ML infrastructure (e.g., model deployment, evaluation, and optimization).
- Experience with Generative AI models or Large Language Models (LLMs) and their application to user-facing products.
- Experience with cloud-based ML platforms and tools, such as vertex AI.
Responsibilities
- Design, implement, and take ownership of specialized Generative AI and Machine Learning solutions (e.g., personalized feedback, multimedia generation) across the full lifecycle from data collection and modeling to evaluation and deployment.
- Design, deploy, and maintain the ML infrastructure and data pipelines required to support the development and scalable serving of conversational education systems.
- Write, test, and maintain robust, high-quality production code for core educational capabilities.
- Collaborate closely with research scientists, product managers, and UX/program managers to define project scope, ensure technical alignment, and deliver highly effective user experiences.
- Act as a technical leader in the implementation of product solutions, contribute to design and code reviews to enforce best practices, and mentor junior engineers.
Other
- Ability to propose, initiate, and lead new, complex, multi-month engineering projects.
- Passion for the mission of improving education globally.
- Display leadership qualities and be enthusiastic to take on new problems across the full-stack.
- Versatile.
