Staff Software Engineer, Machine Learning, Google Assistant

$189,000 - $284,000/Yr

Google - New York, NY

Full-time - Senior

New York, NY

10,001+ employees

Web Search Portals, Libraries, Archives, and Other Information Services

About the position

As a Staff Software Engineer specializing in Machine Learning for Google Assistant, you will be responsible for developing next-generation technologies that enhance user interaction and information retrieval. This role involves working on critical projects that require a blend of software development, machine learning, and leadership skills, with opportunities to switch teams and projects as the business evolves.

Responsibilities

• Write product or system development code.
• Participate in or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Review code developed by other developers and provide feedback to ensure best practices.
• 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.

Requirements

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of experience testing and launching software products.
• 3 years of experience with software design and architecture.
• 5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.

Nice-to-haves

• Master's degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• 3 years of experience working in a complex, matrixed organization involving cross-functional, and/or cross-business projects.

Benefits

• Health insurance
• 401k
• Paid holidays
• Flexible scheduling
• Professional development
• Tuition reimbursement