QualificationsNatural language processingTensorFlowC++Distributed systemsMachine learningDoctoral degreeBachelor’s degreeMaster’s degreeDoctor of Philosophy
Preferred qualifications:
Master’s degree or PhD in Engineering, Computer Science, or a related technical field
5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, and/or natural language processing
5 years of experience building and developing large-scale infrastructure, distributed systems or networks, and/or experience with compute technologies, storage, and/or hardware architecture
3 years of experience in a technical leadership role leading project teams and setting technical direction
3 years of experience working in a complex, matrixed organization involving cross-functional and/or cross-business projects
Familiarity with machine learning
About the job
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.
The Machine Learning (ML) Processing and Analysis team owns and develops infrastructure for processing and analysis of ML data and models. Our portfolio of projects is used to analyze and preprocess data before ML computation, ingest, and process data during ML computation, and analyze models produced by ML computation. Our projects are used to analyze and process data every day, feeding data into Google’s ML hardware, helping users across product areas and ML domains address their use cases.
The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
Responsibilities
Help the team develop the necessary infrastructure for processing and analysis of ML data and models.
Drive the design and development of major functionality that spans the team’s project boundaries.
Collaborate across the Core Machine Learning (ML) organization on integrations with other components of ML infrastructure.
Engage with ML users across different Google product areas to help them improve upon their existing ML workloads.
Collaborate with other engineers to improve the overall experience of ML users at Google.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.