Senior Machine Learning Engineer (GenAI Algos)

talabat
Bristol
3 months ago
Applications closed

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Senior ML Engineer - GenAI specialist position (based in Dubai, UAE - relocation support provided)


Please note: This is an on-site position based in Dubai, United Arab Emirates. We are actively seeking talented Data Scientists who are interested in relocating. We provide the following support:


  • Full visa sponsorship
  • Airline tickets
  • Hotel stay (for up to 30 days)
  • Health insurance


Company Description:


talabat is part of the Delivery Hero Group, the world’s pioneering local delivery platform, our mission is to deliver an amazing experience—fast, easy, and to your door. We operate in over 70+ countries worldwide. Headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index.


Role Summary:


As a data scientist on the algorithms track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will specialize in creating systems that leverage Retrieval-Augmented Generation (RAG), build complex workflows with LangChain/LangGraph, and orchestrate multi-agent systems using frameworks like AutoGen and CrewAI.


What’s On Your Plate?



  • Collaborate and Innovate: Work closely with product managers, data scientists, and software engineers to translate business requirements into technical solutions and contribute to our AI strategy.
  • Develop Advanced RAG Systems: Design, build, and optimize robust RAG pipelines to ground LLMs in external knowledge sources, ensuring factual accuracy and relevance.
  • Build AI Agentic Workflows: Engineer and deploy collaborative multi-agent systems using frameworks like AutoGen or CrewAI to automate complex tasks and decision-making processes.
  • Master Embedding Strategies: Create and manage high-quality vector embeddings for semantic search, text classification, and other NLP tasks. You will work extensively with vector databases like Pinecone, Weaviate, or Chroma.
  • Construct LLM Chains and Graphs: Utilize LangChain or LangGraph to develop, prototype, and productionize complex, stateful applications and workflows powered by LLMs.
  • Model Integration & Deployment: Fine-tune, evaluate, and deploy LLMs and other machine learning models into production environments using MLOps best practices.


What did we order?


  • Experience with cloud platforms (AWS, GCP, or Azure).
  • Bachelor's or Master's degree in Computer Science, AI, Engineering, or a related field.
  • Experience with fine-tuning open-source LLMs (e.g., Llama, Mistral, Falcon).
  • Familiarity with MLOps tools and principles for deploying and monitoring models in production.
  • Proven professional experience as a Machine Learning Engineer, with a strong portfolio of projects.
  • Hands-on experience implementing RAG pipelines and a deep understanding of the underlying architecture.
  • Demonstrable expertise in building applications with LangChain and/or LangGraph.
  • Practical experience developing autonomous agents or multi-agent systems using AutoGen, CrewAI, or similar frameworks.
  • Solid understanding of vector embeddings, similarity search, and experience with vector databases.
  • Proficiency in Python and core ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face).

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