Senior Software Engineer, AI/ML, Google Cloud Compute

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.
• - 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.

Minimum qualifications:

Preferred qualifications:

Qualifications

• Minimum qualifications: - 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). Preferred qualifications: - Master's degree or PhD in Computer Science or related technical field. - 5 years of experience with data structures/algorithms. - 1 year of experience in a technical leadership role. - Experience developing accessible technologies.