Staff Software Engineer, Cloud Machine Learning Compute Services
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Minimum qualifications:
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- 8 years of experience in software development and with data structures/algorithms.
- 5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
- 5 years of experience testing and launching software products, and 3 years of experience with software design and architecture.
Preferred qualifications:
- Experience with Kubernetes, Google Kubernetes Engine, GPU Programming, TensorFlow, and Google Cloud.
- Ability to think creatively and innovate in the context of developer productivity.
- Ability to quickly adapt to new tools, frameworks, and languages.
- Excellent investigative and problem-solving skills, with the ability to break down problems and devise practical AI/ML solutions.
- Passion for learning and staying updated with advancements in AI/ML technologies and their applications.
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.
The Cloud ML Compute Services (CMCS) team is accountable for defining and driving the overall Cloud Machine Learning (ML) Compute IaaS product offering and technical strategy. We are leveraging Google AIs leadership to differentiate Google Cloud Platform (GCP) and delight our customers with the Machine Learning (ML) and High Performance Computing (HPC) platform in the world for talent powered by TPUs, GPUs and CPUs, and all ML frameworks (e.g., Tensorflow, PyTorch, and JAX).
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
- Design and implement new systems from the ground up.
- Build infrastructure and tooling to diagnose model performance issues, remediation steps, and observability for internal and external customers to monitor their workload running on Google Cloud Platform (GCP).
- Partner and empower ML Engineers, Data Scientist, and the ML Frameworks team to optimize the performance of their model on GCP through a set of tooling and capabilities needed for rapid ideation.
- Stay up-to-date with the latest advancements in AI/ML technologies, frameworks, and tools. Evaluate potential impact and relevance to developer productivity.
- Align technical designs across organizations with long-term feasibility and maintainability in mind.
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