Machine Learning Engineer

1 Month ago • 5 Years + • Artificial Intelligence • Data Analyst • Full Stack Development

About the job

Job Description

As a Machine Learning Engineer, you will work on solving technical issues across multiple business areas (e.g., Ads, YouTube, Search, Play, etc.) through business generation. You will collaborate with data scientists, analysts, and Program Managers to create data solutions enabling finance partners to make informed decisions, manage risks and opportunities. Responsibilities include working cross-functionally with data scientists, data engineers, and program managers to implement and deploy machine learning pipelines; improving machine learning scalability, usability, and performance; exploring technologies to deliver business benefits; communicating results to peers and leaders; and advocating processes, standards, and engineering practices. The role requires analyzing large datasets and building expert systems to improve understanding of the web and product performance, involving complex statistical analysis and embedding models into production systems.
Must have:
  • 5+ years experience in ML engineering or data science
  • Experience with TensorFlow, Scikit-learn
  • Agile software development experience
  • Experience with RDBMS (Postgres, MySQL) and big data (Spark)
  • Cross-functional collaboration skills
Good to have:
  • Full-stack development experience
  • Cloud platform experience (GCP)
  • Front-end development (D3.js, React JS)
  • Excellent communication skills
  • Proficiency in Python, Java, Scala, or C++

Minimum qualifications:

  • 5 years of industry experience in a data scientist or machine learning engineer role.
  • Experience with machine learning frameworks such as Tensorflow, Scikit-Learn.
  • Experience in design, implementation, and delivery of scalable build/test/release agile software development cycle.
  • Experience with data processing and management with Relational Database Management System (RDBMS) such as Postgres, MySQL, and big data stacks such as Apache Spark.

Preferred qualifications:

  • Experience in full-stack development for leveraging machine learning solutions.
  • Experience with cloud platforms such as Google Cloud Platform (GCP).
  • Familiarity with front-end development (e.g., D3.js, React JS).
  • Excellent written and verbal communication skills to translate technical solutions and methodologies to executive leadership.
  • Excellent programming skills in at least one of the general programming languages: Python, Java, Scala, C++.

About the job

As a Quantitative Analyst, you will be responsible for analyzing large data sets and building expert systems that improve our understanding of the Web and improve the performance of our products. This effort includes performing complex statistical analysis on non-routine problems and working with engineers to embed models into production systems. You will manage fast changing business priorities and interface with product managers and engineers.

As a Machine Learning Engineer, you will work on solving technical issues across multiple business areas (e.g., Ads, YouTube, Search, Play, etc.) through business generation. You will collaborate with data scientists, analysts, and Program Managers to create data solutions to enable our finance partners to make informed decisions, manage risks and opportunities.

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 technologies to deliver business benefits.
  • Communicate results to peers and leaders.
  • Advocate processes, standards, and engineering practices.
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About The Company

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.

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