Minimum qualifications:
- Experience with Data Analysis, Machine Learning, and Machine Learning Algorithms.
- Experience in technical leadership.
- Experience in coding.
Preferred qualifications:
- Experience developing solutions for real world, large-scale problems.
- Experience using earth observations and environmental data.
- Experience with machine learning technologies such as probabilistic modeling, uncertainty quantification, computer vision and image analysis, transformers, etc.
About the job
As a Software Engineer in Google Research, you’ll set up large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, you will work on real-world problems that span the breadth of computer science, such as machine and deep learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. You will also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with programs at partner universities and technical institutes all over the world.
Responsibilities
- Develop real-world impact-focused projects end-to-end, from conception, to exploration and research, to implementation and operational deployment.
- Develop solutions for real world, large-scale problems, particularly focused on Africa.
- Develop machine learning models in Python (with Tensorflow or JAX) and develop tools and systems to train them at scale on Google’s infrastructure.
- Contribute to real-world deployment and testing of solutions at-scale.
- Be able to take initiative and demonstrate technical leadership to drive research.