Senior Software Engineer & SOC Architect for ML/GPU

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

Benefits offered by this job

Bonus target

Equity

Benefits

Job summary

Google is seeking software engineers to help develop next-generation technologies serving billions of users. You’ll work on projects spanning information retrieval, distributed computing, and AI, with opportunities to switch teams as the company grows.

You will analyze performance data, trace timelines, and support ML workloads across the stack. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.
• 3 years of experience with Computer Architecture, C++, Python, CUDA, GPU Programming, GPU Drivers, System On a Chip, Application-Specific Integrated Circuit.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Responsibilities

• Write and test product or system development code.
• Learn and build an intuitive understanding of existing data collection, analysis, and visualization workflows.
• Support new and exciting ML paradigms (such as horizontal scaling for upcoming TPU chips) by making contributions across the end-to-end stack and analysis tools.
• Partner with Product Area leads to understand model optimization use cases, drive cross functional efforts to deliver on chip profiling requirements, and propose new hardware features.
• Collaborate across Hardware, Driver, Runtime, and Performance Analysis teams and many other stakeholders.

Job description

Google is seeking software engineers to help develop next-generation technologies serving billions of users. You’ll work on projects spanning information retrieval, distributed computing, and AI, with opportunities to switch teams as the company grows.

You will analyze performance data, trace timelines, and support ML workloads across the stack. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.