our company'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 our companys 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 is in charge of all engineering infrastructures for data scientists at Waze including: GenAI framework for Waze internal applications, GenAI for analytics (DataWhiz), GenAI data science and evaluation framework for user-facing Waze features, MLOps framework for training/deploying/serving at scale ML models of Waze, data pipelines framework & infrastructures for running at scale data pipelines, infrastructure as code for data science, and engineering best practices applied in data science.
Waze is where people and technology meet to solve transportation challenges. It's a platform that empowers users to contribute road data and edit Waze maps to improve the way we move about the world. As the social navigation pioneer, Waze leverages mobile technology and a passionate global community to redefine expectations of todays maps.
Responsibilities
Add new features to our GenAI analytics agents serving all of Waze for any data analytics questions.
Research in GenAI for ML research and exploration, backend GenAI models evaluation framework.
Understand ML or Data Science to have knowledge of the users of the framework.
The team is in charge of all engineering infrastructures for data scientists at Waze including: GenAI framework for Waze internal applications, GenAI for analytics (DataWhiz), GenAI data science and evaluation framework for user-facing Waze features, MLOps framework for training/deploying/serving at scale ML models of Waze, data pipelines framework & infrastructures for running at scale data pipelines, infrastructure as code for data science, and engineering best practices applied in data science.
Waze is where people and technology meet to solve transportation challenges. It's a platform that empowers users to contribute road data and edit Waze maps to improve the way we move about the world. As the social navigation pioneer, Waze leverages mobile technology and a passionate global community to redefine expectations of todays maps.
Responsibilities
Add new features to our GenAI analytics agents serving all of Waze for any data analytics questions.
Research in GenAI for ML research and exploration, backend GenAI models evaluation framework.
Understand ML or Data Science to have knowledge of the users of the framework.
Requirements:
Minimum qualifications:
Bachelors degree or equivalent practical experience.
2 years of experience programming in C++, Java, Go or Python, or 1 year of experience with an advanced degree in an industry setting.
2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies.
Preferred qualifications:
1 year of experience in applied Machine Learning (e.g., computer vision, generative AI, LLM).
1 year of experience in data science with focus on analytics, machine learning, and visualization.
Minimum qualifications:
Bachelors degree or equivalent practical experience.
2 years of experience programming in C++, Java, Go or Python, or 1 year of experience with an advanced degree in an industry setting.
2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies.
Preferred qualifications:
1 year of experience in applied Machine Learning (e.g., computer vision, generative AI, LLM).
1 year of experience in data science with focus on analytics, machine learning, and visualization.
This position is open to all candidates.
