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Who We Are VML is a leading creative company that combines brand experience, customer experience, and commerce, creating connected brands to drive growth. VML is celebrated for its innovative and award-winning human-first work for clients including AstraZeneca, Colgate-Palmolive, Dell, Ford, Microsoft, Nestlé, The Coca-Cola Company, and Wendy's. In 2026, VML was named Campaign’s Global Network of the Year and ranked #2 Creative Network of the Year at Cannes Lions. 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. When you click "Submit Application", this will send any information you add below to VML. Before you do this, we think it's a good idea to read through our Recruitment Privacy Policy . California residents should read our California Recruitment Privacy Notice . This explains what we do with your personal data when you apply for a role with us, and, how you can update the information you have provided us with or how to remove it.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.