GenAI Systems Engineer: ML Infra & Innovation

Socket.dev; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google Cloud is seeking software engineers to join our next-gen platform teams in Mountain View. You will work on scalable systems and help shape architecture and reliability for billions of users and developers.

Responsibilities include writing and testing code, collaborating through design reviews, contributing documentation, triaging issues, and designing GenAI-enabled solutions using ML infrastructure.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience programming in Python or C++.
• 3 years of experience with ML infrastructure (model deployment, evaluation, processing, debugging).
• 3 years of experience testing, maintaining, or launching software products.
• 1 year of experience with software design and architecture.
• 1 year of experience with GenAI techniques (LLMs, multimodal, vision) or related concepts.

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, including style guidelines, testing, and efficiency.
• Contribute to existing documentation or educational content and update it with product changes and user feedback.
• Triage product or system issues and debug/track/resolve impacts on hardware, network, or service operations and quality.
• Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs across techniques.

Skills

Python

C++

ML infrastructure

Software testing/launching

Software design/architecture

GenAI techniques

Education

Bachelor's degree or equivalent practical experience

Master's degree or PhD in Computer Science or related field

Job description

Google Cloud is seeking software engineers to join our next-gen platform teams in Mountain View. You will work on scalable systems and help shape architecture and reliability for billions of users and developers.

Responsibilities include writing and testing code, collaborating through design reviews, contributing documentation, triaging issues, and designing GenAI-enabled solutions using ML infrastructure.