Princ Engr-ai Science

Verizon Verizon · Telecom · Chennai, India +2

Principal Engineer (AI Science) at Verizon, focusing on designing and building scalable machine learning models for personalization and recommendation use cases. The role involves end-to-end solution development, working with diverse data types (text, clickstream, sequential), and applying deep learning, particularly transformer-based architectures, for NLP and other applications. The position also requires leadership, mentorship, and contributing to the growth of the data science practice, with a strong emphasis on delivering business benefits through AI-driven solutions.

What you'd actually do

  1. Designing and building scalable machine learning models to meet the needs of given Business engagement. Provide technical thought leadership on model architecture, delivery, monitoring, measurement and model lifecycle best practices.
  2. Working in collaborative environment with global teams to drive solutioning of business problems
  3. Developing end to end analytical solutions, and articulating insights to leadership. Provide data-driven recommendations to business by clearly articulating complex modeling concepts through generation and delivery of presentations.
  4. Analyzing and model both structured and unstructured data from a number of distributed client and publicly available sources.
  5. Assisting with the mentorship and development of junior members. Drive team towards solutions.

Skills

Required

  • Python
  • Pytorch
  • Keras
  • Tensorflow
  • machine learning
  • deep learning
  • statistical modeling techniques
  • natural language processing
  • computer vision
  • audio processing

Nice to have

  • Strong problem-solving skills
  • ability to work on complex, open-ended research problems
  • Excellent communication and collaboration skills
  • ability to work effectively in cross-functional teams

What the JD emphasized

  • production use cases
  • personalization
  • recommendation
  • Deep Learning
  • transformer based architecture
  • NLP
  • image
  • text
  • clickstream
  • sequential data
  • personalisation and recommendation algorithms
  • large scale personalization solutions
  • proven business benefits

Other signals

  • Designing and building scalable machine learning models
  • Developing end to end analytical solutions
  • Analyzing and model both structured and unstructured data
  • Implementing production use cases in the area of personalization including recommendation
  • Deep Learning and application of transformer based architecture for various NLP, image or other use cases
  • Experience in building large scale personalization solutions and with proven business benefits