GENERAL INFORMATION

Req #
WD00087375
Career area:
Artificial Intelligence
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Friday, August 29, 2025
Working time:
Full-time

Additional Locations:

• United States of America - North Carolina - Morrisville

PRIMARY REQUIREMENTS

• At least 7 years of relevant experience of full-time working experience in AI, Machine Learning, MLOps
• Hands on development experience in Python, using related libraries such as Pandas, Pytorch, TensorFlow, Spark
• Experience with Unsupervised and Deep Learning models
• Hands on expertise with MLOps methods and platforms such as MLFlow
• Strong Data Engineering knowledge with technologies such as Apache AirFlow, PySpark
• Experience designing, training and validating ML models
• Experience with testing technologies for various ML Models
• Experience in handling Time Series Data, Anomalies detection, Data Correlation techniques
• Experience in using frameworks such as Prophet, BentoML or other equivalent tools
• Experience with Conversational AI, ChatGPT, Multi language support
• Hands on Experience in Cloud Technologies, preferably AWS
• Good understanding of SaaS platforms and associated technologies
• Proficiency in Containeration, Orchestration of containers, scaling concepts
• Expertise in AWS Bedrock, SageMaker
• Visualization technologies for AI and ML output, BI Reports, Tableau, PowerBI
• Thorough understanding of Agile Development practices, ceremonies
• Prior experience in working for a Product development company
• Excellent communication skills

RESPONSIBILITIES WILL INCLUDE:

• Developing Technical Designs for Machine Learning and Artificial Intelligence features.
• Hands-on development of Solutions in Data Engineering technologies & AI
• Closely collaborate with Architecture teams to establish solutions designed to scale for millions of users.
• Engaging actively with other specializations and compliance processes
• Participating in daily working sessions, and leading workstreams from planning through execution to closure