About Merkle

Merkle, a dentsu company, is a leading data-driven customer experience management (CXM) company that specializes in the delivery of unique, personalized customer experiences across platforms and devices. For more than 30 years, Fortune 1000 companies and leading nonprofit organizations have partnered with Merkle to maximize the value of their customer portfolios. The company’s heritage in data, technology, and analytics forms the foundation for its unmatched skills in understanding consumer insights that drive hyper-personalized marketing strategies. Its combined strengths in consulting, creative, media, analytics, data, identity, CX/commerce, technology, and loyalty & promotions drive improved marketing results and competitive advantage. With more than 14,000 employees, Merkle is headquartered in Columbia, Maryland, with 50+ additional offices throughout the Americas, EMEA, and APAC. For more information, contact Merkle at
1-877-9-Merkle or visit www.merkle.com.

About the role

Are you eager to build a career in the most disruptive innovation of our century, Generative AI?

This role provides an exciting opportunity to work on Merkle’s latest and key market offering GenCX.

GenCx is Merkle’s proprietary GenAI offering that combines foundational models and enterprise customer data to create knowledge models. These models will help better understand customer behavior, interactions and sentiment. This will also accelerate the model development process significantly. Building these knowledge models will require using State of the Art models, libraries, and infrastructure (that are mentioned below). With this you will really be building the application of tomorrow!

Roles & Responsibilities:

• The role involves building AI/ML solutions for business problems across industries (Retail, CPG, Media, Tech.)
• Formulating and executing to the AI/ML roadmap for Merkle’s proprietary Cognitive computing platform
• Drive AI/ML development best practices within the product development team
• Guide and mentor product development teams comprising of Leads to Developers
• Adopting the latest and best in technology stack/libraries (in a rapidly changing landscape) to build better and more efficient AI solutions
• Integrate functions such as ML OPS, Data Ops and Data science integrate to productionalize models
• Build POC solutions for qualified problem statements.

Must Have:

• Large Language Models and Transformers
• Generatively Pretrained Transformers (GPT)
• Machine Learning (linear regression, logistic regression, forecasting)
• Deep Learning (Transformers, Classification, Regression, Collaborative Filtering)
• Databricks, Huggingface, MosaicML

Good to have:

• Cloud implementation – ML Ops
• Vector databases