3 days ago
London, United KingdomEntry Level / Mid Level
Responsibilities
- Write product or system development code.
- Review code developed by other developers and provide feedback on style, accuracy, testability, efficiency, and other best practices.
- Participate in or lead design reviews to select among available technologies.
- Triage, debug, track, and resolve product or system issues by analyzing impacts on hardware, networks, services, and quality.
- Contribute to and update technical documentation or educational content based on product or program changes and user feedback.
- Design and operate distributed computing systems for large-scale AI/ML workloads.
- Implement machine learning algorithms and techniques and develop large-scale data infrastructure, pipelines, or tooling.
Requirements
- Bachelor’s degree or equivalent practical experience.
- At least 2 years of software development or ML research experience, or equivalent qualifying education credit such as internships, student research, or pre-graduate work experience.
- Experience conducting research to solve AI or ML problems.
- Experience implementing machine learning algorithms or techniques and using machine learning frameworks such as Jax, PyTorch, or Triton.
- Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
- At least one scientific publication submission to a conference, journal, or public repository, including work in machine learning or computational neuroscience.
- Preferred experience with distributed storage systems, relational databases, and schema or query design, including PostgreSQL, Cloud Spanner, Bigtable, Cassandra, or DynamoDB.
- Preferred experience with large-scale data pipelines and distributed batch or streaming frameworks such as Apache Beam, Spark, Dataflow, Ray, or Flink.
- Preferred experience building data infrastructure, pipelines, or tooling within an ML research environment.
- Familiarity with a compiled systems or backend language such as C++, Rust, Go, or Java, or with media codecs for video, audio, or images.
Tech Stack
Categories
Data EngineeringML Engineering
About Google
Google builds consumer and enterprise software and services including Search, Android, YouTube, Chrome, Maps, Gmail, and Google Cloud. Its business model centers on digital advertising and paid cloud, software, and hardware offerings (e.g., Pixel and Nest) for consumers, developers, and organizations. Founded in 1998 and headquartered in Mountain View, California, Google operates globally as a subsidiary of Alphabet Inc.