Engineer II-AI/ML Engineering

Key Skills

Aartificial intelligence, Analytical and Problem solving, Apache Airflow, Apache Oozie, Continuous Integration & Continuous Delivery - CI/CD, Dataproc, Google BigQuery, Google Cloud Platform (GCP), Machine learning techniques, MLOps tools, PySpark, Python Programming

Job Description

When you join Verizon

Verizon is one of the world’s leading providers of technology and communications services, transforming the way we connect around the world. We’re a human network that reaches across the globe and works behind the scenes. We anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together—lifting up our communities and striving to make an impact to move the world forward. If you’re fueled by purpose, and powered by persistence, explore a career with us. Here, you’ll discover the rigor it takes to make a difference and the fulfillment that comes with living the #NetworkLife.

What you’ll be doing...

• Monitoring and maintaining the performance and health of deployed machine learning models, addressing issues related to model performance, data drift, and overall reliability.
• Keeping track of all batch models running in GCP platform.
• Model Performance Metrics validation and fixing/reporting on drift.
• Model Feature Drift Monitoring and actions to fix.
• Partnering closely with the data engineering, data science and DevOps teams to design and deploy end-to-end machine learning pipelines in production.
• Data science models testing, validation and tests automation.
• Pipeline orchestration in GCP Platform.

What we’re looking for...

As a Machine Learning Engineer with production-quality code in deployment. Communicate with a team of data scientists, data engineers and architect, document the processes.

You’ll need to have:

• Bachelor’s degree or one or more years of work experience.
• Experience as ML Engineer.
• Experience on GCP ML stacks.
• Experience with Python/Pyspark and MLOps Frameworks, Domino, DataRobot, Airflow, GCP Data Proc, BigQuery, Oozie etc.
• Knowledge on ML Pipeline orchestration using CI/CD.

Even better if you have one or more of the following:

• Google Certified on ML Engineer or Data Engineer or Architect.
• Outstanding analytical and problem-solving skills.

Where you’ll be working

In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager.

Scheduled Weekly Hours: 40