Staff AI/ML Engineer - Shopping Growth & Insights

Socket.dev; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google is hiring software engineers to build next-generation technologies that scale for billions of users. You will work across information retrieval, distributed systems, ML, and security, taking on challenging problems and switching teams as needed to drive impact.

Responsibilities include shaping ML solutions, optimizing infrastructure, and guiding model training and data processing while collaborating with a global, fast-paced team.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with ML design, ML infrastructure (model deployment, evaluation, data processing, debugging, fine tuning).
• Experience integrating generative AI tools or LLM interfaces into workflows.

Responsibilities

• Design, develop, test, deploy, maintain, and enhance large scale software solutions.
• Provide technical leadership on high-impact projects and manage priorities, deadlines, deliverables.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines; coach distributed engineers.
• Lead design and implementation of ML solutions, optimize ML infrastructure, and guide data processing strategies.

Skills

ML design & infrastructure

Reinforcement learning

Speech/Audio ML

Model deployment & data processing

Education

Bachelor’s degree or equivalent practical experience

Master’s degree or PhD in Engineering, Computer Science, or related field

Job description

Google is hiring software engineers to build next-generation technologies that scale for billions of users. You will work across information retrieval, distributed systems, ML, and security, taking on challenging problems and switching teams as needed to drive impact.

Responsibilities include shaping ML solutions, optimizing infrastructure, and guiding model training and data processing while collaborating with a global, fast-paced team.