Senior AI/ML Engineer - Cloud-Scale Leadership & Impact

Google; New York (NY); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Paid time off - 20 days/year

Sick time - 40 hours/year

Maternity leave - 28-30 weeks

Baby bonding leave - 18 weeks

Holidays - 13 paid days/year

Job summary

Google is seeking a software engineer to design, build, and deploy large-scale systems with emphasis on ML and AI infrastructure. You will contribute to multiple projects, lead technical direction, and collaborate across teams to deliver high-impact solutions.

The role emphasizes end-to-end development, model deployment, data processing, and ongoing optimization of ML workflows in a fast-paced, high-scale environment.

Qualifications

• Bachelor’s degree or equivalent practical experience is required.
• 8 years of experience in software development.
• 5 years of experience with speech/audio, reinforcement learning, ML infrastructure, or related ML field.
• 5 years leading ML design and optimizing ML infrastructure (deployment, evaluation, data processing, debugging, fine tuning).
• 5 years of testing and launching software products.
• 3 years of experience with software design and architecture.

Responsibilities

• Design, develop, test, deploy, maintain, and enhance large scale software solutions.
• Provide technical leadership on high-impact projects and manage priorities.
• Coordinate across teams to align goals, outcomes, and timelines; coach distributed engineers.
• Lead design and implementation of solutions in ML areas, optimize infrastructure, guide model optimization and data processing.

Skills

Software development

ML design

Leadership

Testing & launching software

Education

Bachelor's degree or equivalent practical experience

Tools

ML infrastructure

Model deployment

Data processing

Job description

Google is seeking a software engineer to design, build, and deploy large-scale systems with emphasis on ML and AI infrastructure. You will contribute to multiple projects, lead technical direction, and collaborate across teams to deliver high-impact solutions.

The role emphasizes end-to-end development, model deployment, data processing, and ongoing optimization of ML workflows in a fast-paced, high-scale environment.