Software Engineer, Onefleet Demand Planning

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience in software development.
  
• 3 years of experience coding with Java and working with Java Development tools.
• 3 years of experience with Java design patterns.
• 2 years of experience with database design.
• 2 years of experience with data structures and algorithms in either an academic or industry setting.

Preferred qualifications:

• Experience coding in one of the following programming languages including but not limited to: C, C++, Python, or Golang.
• Experience in one or more of the following: architecting or developing distributed systems, concurrency, multi-threading, or synchronization.
  
• Experience with Angular, Boq, data analysis, and mathematical optimization.

The ML, Systems, and Cloud AI Google’s Demand and Capacity Planning tooling organization is responsible for ensuring that Google has the right infrastructure resources in the right place at the right time to support the company's goals. This includes developing and implementing strategies, processes, and tooling for managing demand and capacity across all of Google’s infrastructure, encompassing machine learning, Cloud, and standard fleets. This organization is critical to Google's success, as it directly impacts the company's ability to innovate and deliver products and services to its users. The team works to optimize resource allocation, improve efficiency, and ensure that Google's infrastructure is both scalable and reliable.

Our team is responsible for capacity demand forecasting and demand planning, as well as visibility and governance tools for driving supply chain delivery of resources, for all of Google. Working closely with our various partners, our north star vision is to deliver a frictionless capacity experience for our customers that results in a reliable, high quality demand signal to drive the right amount (for the customer and for Google) of capacity, in the right place, at the right time.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary range for this full-time position is $166,000-$244,000 + 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.

• Design and implement optimization strategies to handle emerging business requirements, supporting customer reliability and supply chain resilience in the fleet.
• Drive the technical vision to architect the solutions to be reusable across multiple product types, product areas, and classes of feature.
• Collaborate with the business team to identify key opportunities to renovate the deployed fleet, identify supply chain planning inefficiencies, and propose innovative solutions.
• Promote standardization of modeling tools and pipeline execution infrastructure.