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Software Engineer III, ML Infrastructure, Google Cloud
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Job updated about 20 hours ago
The employer was active 5 months ago
Job Description
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Pune, Maharashtra, India; Hyderabad, Telangana, India; Bengaluru, Karnataka, India.
Vertex Training offers data scientists and machine learning engineers managed services to develop, train, and tune machine learning models. This flexible platform opens access to hardware and frameworks for developing machine learning models, without requiring users to manage the underlying resources. Vertex Training assists data scientists in running and monitoring their machine learning workloads, while still giving them the flexibility to bring on any type of model or code they need.
The team’s mission is to build a Machine Learning (ML) Training platform that empowers customers to develop scalable and performant ML models.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.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.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages (e.g., Python, C++ or Java).
- Experience in machine learning infrastructure.
- Experience in distributed machine learning.
- Experience with distributed computing and Cloud APIs.
Preferred qualifications:
- Experience with large-scale distributed machine learning, ML performance optimizations, etc.
- Experience with ML frameworks (e.g., PyTorch).
- Experience working on Cloud and ML products.
- Experience in back-end system development and familiarity with common Google Infrastructure.
- Experience with OSS AI/ML Job scheduling software.
About the job
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.Vertex Training offers data scientists and machine learning engineers managed services to develop, train, and tune machine learning models. This flexible platform opens access to hardware and frameworks for developing machine learning models, without requiring users to manage the underlying resources. Vertex Training assists data scientists in running and monitoring their machine learning workloads, while still giving them the flexibility to bring on any type of model or code they need.
The team’s mission is to build a Machine Learning (ML) Training platform that empowers customers to develop scalable and performant ML models.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
- Build components to enable large-scale distributed training with focus on usability, performance and resiliency.
- Collaborate with partner teams, dependencies (e.g., Google Compute Engine (GCE), Google Kubernetes Engine (GKE), Cloud Tensor Processing Unit (Cloud TPU), Core Infra, CoreML) to develop pre-training/post-training software to enable customer run reliable and performant workloads.
- Work with Product Team, Account teams and customers to identify key pain points, define scope of the problems, translate them into projects and lead them to execution.
- Contribute to product excellence, and improve overall product quality and user experience.
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Google
Information Services
> 5000 people
About us
Google’s mission is to organize the world‘s information and make it universally accessible and useful.
Since our founding in 1998, Google has grown by leaps and bounds. From offering search in a single language we now offer dozens of products and services—including various forms of advertising and web applications for all kinds of tasks—in scores of languages. And starting from two computer science students in a university dorm room, we now have thousands of employees and offices around the world. A lot has changed since the first Google search engine appeared. But some things haven’t changed: our dedication to our users and our belief in the possibilities of the Internet itself.