We are seeking a hands-on GenAI Engineer to join our team and lead the design and implementation of Generative AI-powered prototypes across Media supply chain.

- The role will focus on building out machine learning solutions for WBDs content and Ad platform.

- Primary focus will be on unlocking machine learning opportunities in media supply chain, captioning services, ad conditioning, metadata extraction and building foundational machine learning training and inference pipelines at scale.

- You will lead by example and define the best practices, will set high standards for the entire team and for the rest of the organization.

- You have a successful track record for ambitious projects across cross-functional teams.

- You are passionate and results oriented.

- You strive for technical excellence and are very hands-on.

- Your co-workers love working with you.

- You have built respect in your career through concrete accomplishments.

- Build cutting-edge capabilities utilizing machine learning and data science (e.g. , large language models, computer vision models, advanced ad & content targeting, etc.

- Lead design and development of machine learning systems.

- Design and implement prompt-based applications using LLMs (e.g. , OpenAI, Claude, Mistral).

- Build pipelines for RAG (Retrieval-Augmented Generation) using tools like LangChain, LlamaIndex, or Haystack.

- Integrate LLMs with external APIs, structured databases, and unstructured content (PDFs, contracts, metadata).

- Use embedding models and vector stores (e.g. , Pinecone, Weaviate, FAISS) for semantic search.

- Develop reusable modules for key initiatives like Cairo, Rights Summarization, Deal Assist, and Contract QA automation.

- Collaborate with TPMs, domain SMEs, and software engineers to define and implement POCs.

- Monitor and evaluate GenAI system outputs for factual accuracy and hallucination risk.

What to Bring : .

- 5-8 years of experience designing, building AI/ML or GenAI projects.

- Strong programming skills in Python, Java, or Golang.

- Good understanding of Distributed systems, design and architecture.

- Familiarity with LLM APIs (e.g., OpenAI, Anthropic, Cohere, HuggingFace Transformers).

- Proficiency in operating machine learning solutions at scale, covering the end-to-end ML workflow.

- Experience with Deep Learning, NLP, LLMs, Reinforcement Learning, Causal Inference.

- Good knowledge of ML tools and frameworks (TensorFlow, Keras, pyTorch, scikit-learn, Spark,.

- Exposure to RAG (Retrieval-Augmented Generation), vector databases (e.g., FAISS, Pinecone, Weaviate), and embedding techniques.

- Experience with GenAI frameworks like LangChain, LlamaIndex, or PromptLayer.

- Familiarity with real-world ML systems (configuration, data collection, data verification, feature extraction, resource and process management, analytics, training, serving, validation, experimentation, monitoring).

- Experience with offline experimentation and A/B testing.

- Understanding of batch and streaming data processing techniques.

- Knowledge of AWS or similar cloud platforms.

- Deep understanding of media supply chain workflowsincluding content ingestion, metadata, rights, and distribution.

- Masters/ Bachealors in Computer Science or related discipline.

What We Offer :

- A Great Place to work.

- Equal opportunity employer.

- Fast track growth opportunities.