Description
We are seeking an experienced Software Engineer for a fixed-term contract to join the Energy Grids team at Google DeepMind. You will work at the cutting edge of power systems and machine learning, developing and deploying innovative AI solutions to optimize the operation of electrical power grids.
Your key responsibilities will include:
Designing, implementing, and maintaining robust and reliable systems and workflows for generating large-scale synthetic and real datasets of power grid optimization problems.
Designing and implementing rigorous unit, integration, and system tests to ensure the reliability, accuracy, and maintained performance of our models and software, with a focus on data pipelines.
Maintaining and contributing to our machine learning codebase, ensuring efficient data structures and seamless integration with our power system models and optimization solvers.
Ensuring the codebase supports ongoing experimentation, while simultaneously increasing scalability, robustness, and reliability via improved integration testing and performance benchmarking.
Working closely and collaboratively with a team of engineers, research scientists, and product managers to deliver real-world impact.
To be successful in this role, you will need:
A Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience.
Excellent proficiency in C++, Python, or Jax.
Demonstrated experience developing or utilizing solutions for robustness or quality assurance within software and/or ML systems.
Experience processing, generating, and analyzing large-scale data, e.g. for ML applications.
Proven ability to discuss technical ideas effectively and collaborate in interdisciplinary teams.
Motivated by the prospect of real-world impact and focused on excellence in software development.
Preferred qualifications include experience with Google's technical stack and/or Google Cloud Platform (GCP), familiarity with modern hardware accelerators (GPU / TPU), experience with modern ML training frameworks, such as Jax, and experience in developing software in a translational research or production setting.