Software Engineer, ML

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience programming in Python and C++.
• Experience in developing and maintaining backend software systems.

• Master's degree or PhD in Computer Science or related technical fields.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
• Experience with data engineering technologies such as Apache Flume.
• Experience with data structures and algorithms, or implementing core ML concepts.
• Experience in cloud computing, including one or more of the following: public, private cloud, compute, storage, networking, software, platform/infrastructure-as-a-service.

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.

As a Software Engineer, you will contribute to the development of forecasting and capacity planning tools and infrastructures for Google, as well as other time series research and services using AI/ML/statistics. Through this work you will not only help Google run as efficiently as possible, but you will also help us to advance our capabilities and the time series forecasting and demand planning.

You will drive foundational data science innovation and engineering standardization to enable fast, accurate, scalable and verifiable solutions in time series forecasting, and capacity planning applications. You will drive efficient utilization of Google's compute and storage resources through standardized processes and tools for resource forecasting, capacity planning, and risk sharing across the fleet.

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.

The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

• Apply statistical and AI/ML methods to solve tests related to ML, compute, storage, network, and data center capacity efficiency for Google’s internal services and Google Cloud Platform.
• Collaborate across Platforms Engineering, Systems Infrastructure, and SRE teams to optimize resource deployment and support internal teams with time series forecasting tools.
• Develop problem-solving models to drive strategic decisions regarding total cost of management and workload resource optimization.
• Research, implement, test, and serve optimally structured models that power a variety of engineering tools and dashboards.
• Contribute…