Asks for

The ad says“Familiarity with deploying AI models via microservices or APIs.”
The ad says“Experience with MLOps pipelines and platforms like AWS SageMaker, Azure AI Search, or similar.”
The ad says“Experience with MLOps pipelines and platforms like AWS SageMaker, Azure AI Search, or similar.”
The ad says“Solid understanding of Large Language Models (LLMs), embeddings, and semantic search technologies.”
The ad says“Strong practical experience with leading Machine Learning frameworks such as TensorFlow, PyTorch, and Hugging Face.”
The ad says“Experience with LangChain and LangGraph.”
The ad says“Experience with LangChain and LangGraph.”
The ad says“Solid understanding of Large Language Models (LLMs), embeddings, and semantic search technologies.”
The ad says“Familiarity with deploying AI models via microservices or APIs.”
The ad says“Experience with MLOps pipelines and platforms like AWS SageMaker, Azure AI Search, or similar.”
The ad says“Who we’re looking for: We are seeking an experienced AI/ML Engineer with a minimum of 5 years of expertise to join our innovative technology team. In this pivotal role, you will be responsible for designing, training, and optimizing AI models, with a strong focus on Natural Language Processing (NLP) for real-time content summarization, recommendation, and conversational UIs. You will implement cutting-edge techniques like Retrieval-Augmented Generation (RAG) and fine-tune transformer-based models, collaborating closely with backend and data engineering teams to ensure seamless deployment and maintenance of brand tone and content accuracy in all AI outputs.”
The ad says“Expert proficiency in Python and robust data handling libraries such as Pandas and NumPy.”
The ad says“Expert proficiency in Python and robust data handling libraries such as Pandas and NumPy.”
The ad says“Expert proficiency in Python and robust data handling libraries such as Pandas and NumPy.”
The ad says“Strong practical experience with leading Machine Learning frameworks such as TensorFlow, PyTorch, and Hugging Face.”
The ad says“Apply Retrieval-Augmented Generation (RAG) for intelligent response generation from dynamic content sources.”
The ad says“Solid understanding of Large Language Models (LLMs), embeddings, and semantic search technologies.”
The ad says“Strong practical experience with leading Machine Learning frameworks such as TensorFlow, PyTorch, and Hugging Face.”
The ad says“Fine-tune transformer-based models (e.g., BERT, T5) using domain-specific datasets to achieve optimal performance.”

Who We Are

VML is a global creative company that combines brand experience, customer experience, and commerce to create connected brands that drive growth. Guided by a Human First philosophy, VML is known for its innovative work for brands and consistently ranks among the world’s leading creative companies, including the WARC Creative 100. VML’s global network spans 55+ markets with principal offices in Buenos Aires, Kansas City, London, New York, São Paulo, Shanghai and Singapore.

VML is part of WPP, the trusted growth partner for the world's leading brands. Powered by exceptional talent and our agentic marketing platform WPP Open, WPP unites cutting-edge media intelligence and data solutions, creativity, production, enterprise solutions and expert strategic counsel.

For more information, please visit www.vml.com and follow along on  LinkedIn #WeAreVML.

Who we’re looking for: We are seeking an experienced AI/ML Engineer with a minimum of 5 years of expertise to join our innovative technology team. In this pivotal role, you will be responsible for designing, training, and optimizing AI models, with a strong focus on Natural Language Processing (NLP) for real-time content summarization, recommendation, and conversational UIs. You will implement cutting-edge techniques like Retrieval-Augmented Generation (RAG) and fine-tune transformer-based models, collaborating closely with backend and data engineering teams to ensure seamless deployment and maintenance of brand tone and content accuracy in all AI outputs.

What you’ll be doing:

Design, train, and optimize AI models specifically for real-time content summarization and recommendation.
Implement advanced Natural Language Processing (NLP) techniques to enhance conversational UI and predictive interactions.
Apply Retrieval-Augmented Generation (RAG) for intelligent response generation from dynamic content sources.
Fine-tune transformer-based models (e.g., BERT, T5) using domain-specific datasets to achieve optimal performance.
Collaborate closely with backend and data engineering teams to streamline model deployment within a production-grade environment.
Ensure that brand tone and content accuracy are meticulously maintained throughout all AI-generated outputs.

What you’ll need:

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
5–7 years of progressive experience in AI/ML engineering, with a strong and proven focus on Natural Language Processing (NLP).
Strong practical experience with leading Machine Learning frameworks such as TensorFlow, PyTorch, and Hugging Face.
Experience with LangChain and LangGraph.
Experience with MLOps pipelines and platforms like AWS SageMaker, Azure AI Search, or similar.
Solid understanding of Large Language Models (LLMs), embeddings, and semantic search technologies.
Expert proficiency in Python and robust data handling libraries such as Pandas and NumPy.
Familiarity with deploying AI models via microservices or APIs.
Preferred Qualifications:
Understanding of branding, tone, and the user experience (UX) implications in AI-generated content.
Experience working with headless CMS (Content Management Systems) and structured content datasets.
Knowledge of ethical AI principles and prompt engineering best practices.

Additional Competencies:

AI/ML Engineering
Natural Language Processing (NLP)
Large Language Models (LLMs)
MLOps & Deployment
Python & Data Science
Transformer Models
Content Summarization & Recommendation
Brand & Content Integrity

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office an average of four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.

WPP (VML) is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

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Asks for

Values

Who We Are