Senior ML Engineering Specialist

Google
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Job Description

Minimum qualifications:

  • 8 years of industry experience with 5 years in machine learning or software engineering
  • Experience in one of the general programing languages such as Python, Java, Scala, C++
  • Experience in design, implementation and delivery of scalable build/test/release agile software development cycle

Preferred qualifications:

  • Industry experience with data processing and management with both RDBMS such as Postgres, MySQL and big data stacks such as Apache Spark
  • Experience with machine learning frameworks such as Tensorflow, Scikit-Learn
  • Full-stack development experience for end-to-end machine learning solutions
  • Experience with cloud platforms
  • Familiarity with front end development such as D3.js, React JS a plus
  • Effective communication (written and verbal) to translate technical solutions and methodologies to senior leadership

About the job

The Finance Data & Analytics (DnA) team combines business acumen, technology, and innovation to organize data, enable insights, and create data driven and efficient Finance organization in Google. As part of this team, you will have a unique opportunity to gain perspectives on Google’s core businesses, services and the products.

At Google, data drives all of our decision-making. As a Senior ML Engineering Specialist, you will work on strategic business challenges across multiple business areas (ex. Google Ads, YouTube, Search, Google Play, etc.) through the lens of monetization. You will collaborate with data scientists, analysts, and Product Managers to create end-to-end data solutions to enable our finance partners to make informed decisions, manage risks, and opportunities. You will demonstrate scaled ML Deployment and MLOps experience, and an understanding of our business models to address complex data problems.

As part of the growing DnA data science team, we are particularly excited about bringing on folks interested in advancing their data science & ML skills and collaborating with others.

The name Google came from googol, a mathematical term for the number 1 followed by 100 zeros. And nobody at Google loves big numbers like the Finance team when providing in depth analysis on all manner of strategic decisions across Google products. From developing forward-thinking analysis to generating management reports to scaling our automated financial processes, the Finance organization is an important partner and advisor to the business.

Responsibilities

  • Work cross-functionally with data scientists, data engineers, and program managers to understand, implement and deploy machine learning pipelines
  • Improve machine learning scalability, usability, and performance
  • Explore the state-of-the-art technologies and apply them to deliver business benefits
  • Effectively communicate results to peers and leaders
  • Advocate processes, standards, and engineering practice

Company Info.

Google

Google LLC is a multinational technology company headquartered in the United States that specializes in various fields, including search engine technology, cloud computing, online advertising, quantum computing, e-commerce, computer software, artificial intelligence, and consumer electronics. With its market dominance, data collection, and technological advancements in AI.

  • Industry
    E-commerce,Artificial intelligence,Internet services,Cloud computing,Computer software,Advertising,Computer hardware,Consumer electronics
  • No. of Employees
    139,995
  • Location
    1600 Amphitheatre Parkway, Mountain View, CA 94043, USA
  • Website
  • Jobs Posted

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Google is currently hiring Senior ML Engineering Specialist Jobs in Chicago, IL, USA with average base salary of $160,000 - $240,000 / Year.

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