Software Engineer, Machine Learning Profiler

$161,000 - $239,000/Yr

Google - Sunnyvale, CA

Full-time - Mid Level

Sunnyvale, CA

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

About the position

As a Software Engineer specializing in Machine Learning Profiling at Google, you will be instrumental in developing next-generation technologies that enhance how users interact with information. This role involves working on critical projects that require a deep understanding of software development, data structures, and algorithms, while also providing opportunities to switch teams and projects as the business evolves. You will leverage your technical expertise to manage project priorities, deadlines, and deliverables, while designing, developing, testing, deploying, maintaining, and enhancing software solutions. Your work will include collecting and analyzing profile data to provide expert-level visualizations and actionable insights for users.

Responsibilities

• Learn and build an intuitive understanding of existing data collection, analysis, and visualization workflows.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Support new and exciting Machine Learning (ML) paradigms such as horizontal scaling for upcoming Tensor Processing Unit (TPU) chips by making contributions across the 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 with many other stakeholders.

Requirements

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
• 3 years of experience testing, maintaining, or launching software products.
• 1 year of experience with software design and architecture.

Nice-to-haves

• Master's degree or PhD in Computer Science, or a related technical field.
• 1 year of experience in a technical leadership role.
• Experience with Graphics Processing Unit (GPU) architecture, Compute Unified Device Architecture (CUDA) development, and GPU kernel performance optimization.
• Experience in machine learning.
• Experience developing accessible technologies.
• Familiarity with CUDA Profiling Tools Interface (CUPTI) libraries.

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• 401(k) plan
• Paid holidays
• Paid time off
• Employee stock purchase plan
• Tuition reimbursement
• Professional development opportunities