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Staff Software Engineer, ML Telemetry

Staff Software Engineer, ML Telemetry

1 Month ago • 8-13 Years • Full Stack Development • Research & Development • Artificial Intelligence

About the job

7 skills required for this role

Test your skills to join the top 1% applicants for this job

tensorflow

cpp

algorithms

data-structures

sql

data-analytics

networking

Job Description

As a Staff Software Engineer, ML Telemetry at Google, you'll drive improvements to the ML software and hardware stack using telemetry and metrics. Responsibilities include measuring and reporting ML fleet efficiency, identifying optimization opportunities, and driving improvements via changes to Core ML products and services. You will measure fleetwide adoption of Core ML products, collect metrics for the ML roadmap, and provide data-driven feedback to various teams. This role requires extensive experience in software development, distributed systems, and data analytics, along with expertise in machine learning and system optimization. The position involves building and maintaining large-scale infrastructure and developing data pipelines.

Must have:

8+ years software development experience
Experience with data structures/algorithms
5+ years building large-scale infrastructure
Experience with data analytics (SQL)
Experience with Machine Learning

Good to have:

Experience with backend programming (C++)
Experience with TensorFlow
Experience with Compilers, Computer Architecture
Experience with System Optimization techniques

Minimum qualifications:

Bachelor's degree in Computer Science or related technical field, or equivalent practical experience.
8 years of experience in software development, and with data structures/algorithms.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
5 years of experience building and developing large-scale infrastructure, distributed systems or networks, and/or experience with compute technologies, storage, and/or hardware architecture.

Preferred qualifications:

Experience with backend programming (C++) and data analytics (SQL) for development of instrumentation and data pipelines.
Experience in Machine Learning (e.g., theory, TensorFlow, and other tools).
Experience with Compilers, Computer Architecture, Distributed Systems or related fields.
Experience with System Optimization techniques.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

Drive continuous improvements to the Machine Learning software and hardware stack through telemetry and metrics.
Measure and report the efficiency of the ML fleet, generate and collect metrics that help identify optimization opportunities, and drive improvements via changes to Core ML products and services.
Measure and report the fleetwide adoption of Core ML products and services.
Collect metrics to inform the ML software and hardware roadmap.
Provide data driven actionable feedback to ML job owners, product area resource planners, and Fleet resource planners.

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About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.