Engineering Manager, Machine Learning Infrastructure, Google Cloud

3 Months ago • 8-13 Years • Research & Development

Job Summary

Job Description

As an Engineering Manager for Machine Learning Infrastructure at Google Cloud, you'll lead and mentor a team of engineers, setting priorities aligned with broader organizational goals. Responsibilities include managing a large product budget, overseeing international deployments of large-scale projects, and developing mid-term technical roadmaps. You'll design and vet systems, contribute to code development, review code for best practices, and provide feedback and coaching to team members. The ideal candidate possesses strong technical expertise in distributed systems, large-scale data processing, and machine learning, along with proven leadership experience.
Must have:
  • 8+ years software development experience
  • 5+ years building large-scale systems
  • 3+ years technical leadership
  • 2+ years people management
  • Strong communication & collaboration skills
Good to have:
  • Master's/PhD in relevant field
  • 3+ years experience with ML algorithms & tools
  • 3+ years experience in complex organizations

Job Details


Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 5 years of experience building and developing Large Scale Distributed Systems, Large Scale Data Processing, or related infrastructure.
  • 3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 3 years of experience with machine learning algorithms and tools (e.g. TensorFlow), or applied ML (e.g., deep learning, natural language processing).
  • 3 years of experience working in a complex, matrixed organization.

About the job

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

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

  • Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams. 
  • Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching. 
  • Develop the mid-term technical goal and roadmap within the scope of your teams. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
  • Design, guide and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems. 
  • Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).

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