Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 2 years of experience with Large Language Models.
- 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- 2 years of experience with data structures or algorithms.
- Experience developing accessible technologies.
- Experience with reinforcement learning.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
The team works on new ways to search, with a focus on LLM modeling.
The goal is to find new under-explored opportunities to apply LLMs, make them work in the real world, and collaborate with other teams to scale them to their full potential.
Responsibilities
- Write a product or system development code.
- Collect training data, and evaluate its quality.
- Design and build evaluations.
- Deploy models to production, measure and optimize their latency.
- Run evaluation, analyze results and suggest modeling improvements.
