Job Description
The position designs ML infrastructure using Python or C++ to deploy models in areas like speech and reinforcement learning. Engineers test systems for reliable services in cloud computing. This supports Googlers and customers with scalable AI solutions.
Google advances AI and infrastructure through TPUs and Vertex AI. The company delivers breakthroughs for global services and platforms. It shapes hyperscale computing with teams in research and operations.
Engineers write code in Python or C++, reviewing designs for speech, reinforcement learning, and model evaluation. They debug issues in data processing and networks. Work involves ML specialists and infrastructure teams. One challenge is maintaining efficiency in large-scale deployments.
The base salary ranges from $166,000 to $244,000 plus bonus, equity, and benefits. The role is full-time without specified locations.
Responsibilities
- Write and test product or system development code
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency)
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality
- Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field
Requirements
- Bachelor’s degree or equivalent practical experience
- 5 years of experience programming in Python or C++
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture
- 3 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging)
- Master's degree or PhD in Computer Science or related technical field preferred
- 5 years of experience with data structures/algorithms preferred
- 1 year of experience in a technical leadership role preferred
- Experience developing accessible technologies preferred