Senior Software Engineer, Storage AI/ML
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- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 5 years of experience with software development in one or more programming languages. Rust, Java, Python.
- 5 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- Experience with Storage infrastructure and AI/ML infra (e.g., TensorFlow), artificial intelligence, deep learning, inference frameworks, training frameworks.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 5 years of experience with data structures and algorithms.
- 1 year of experience in a technical leadership role.
- Experience developing accessible technologies.
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 Storage AI/ML Solutions team leverages deep domain expertise to optimize Cloud Storage for cutting-edge AI/ML workloads at planet-scale. We empower customers to maximize GCP performance while assisting internal teams in positioning GCP Storage as the industry's leading solution. By engineering specialized AI client libraries and publishing credible benchmarks, the team provides metrics for throughput, latency, and scalability. Additionally, we actively collaborate with the open-source community to bridge technical gaps and ensure seamless integration with GCP.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $174000 - $253000 (USD) + 15% bonus target + bonus + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Senior SWE in the Tessellation team where main charter for AI/ML storage solutions: focusing on AI/ML solutions such as client side distributed caching, benchmarking, performance investigation and storage optimizations.
- Lead feature design, develop and tune benchmarks for GCP Storage systems with the goal to make GCP Storage the best for AI/ML workloads.
- Work closely with various teams across GCP, including core GCS, File Solutions, GKE, Cloud ML Compute Services (CMCS), and Networking to driving storage innovation for AI/ML.
- Build deep technical expertise in file systems, operating systems, performance engineering, and the rapidly evolving AI/ML landscape.
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