Software Engineer III, Kaggle, AI/Machine Learning (google)
Job posting number: #154593 (Ref:76930857142493894)
Job Description
Qualifications
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, and with data structures or algorithms.
- 2 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning or natural language processing.
- Experience with Large Language Models, NLP, or Generative AI.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing accessible technologies.
- Experience with C# and JavaScript.
- Familiarity with machine learning concepts and algorithms.
- Strong communication and collaboration skills.
Summary
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, and with data structures or algorithms.
- 2 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning or natural language processing.
- Experience with Large Language Models, NLP, or Generative AI.
Description
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.
Shape the future of empirical validation for AI and ML at massive scale at Kaggle! As a member of the new Kaggle Research team – a combined team of research scientists and engineers – you will work on Kaggle’s Research priorities, help innovate in Kaggle’s leading platform for ML competitions, datasets and models, and establish Kaggle Research as the leader in building earned trust through community validation of AI.
Kaggle partners with organizations around the world to bring the most interesting and important problems from all domains and disciplines to our community. Our vision is to activate our community to create the knowledge and resources the world needs to build AI responsibly and effectively.
The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.
Responsibilities
- Collaborate with the Kaggle Research team to design and implement software systems and tools that support the cutting edge of benchmarking and evaluation AI/ML. Collaborate with Google DeepMind Researchers and external researchers to create and host valuable AI evaluations and benchmarks on Kaggle.
- Develop and maintain software infrastructure for running Kaggle competitions and benchmarks.
- Work with the Kaggle Competitions team to expand Kaggle's competitions platform to host and run LLM Benchmarks and community evaluations.
- Contribute to the development and deployment of new research methods and algorithms for AI and ML.
- Publish research papers and present findings at conferences and workshops. Collaborate with engineering, design, and product leadership to improve Kaggle's product for research priorities.