C01 - Machine Learning Engineer

About the Role

• We are seeking a Machine Learning Engineer to help prototype, evaluate, and operationalize emerging AI technologies for airport use cases.
• You will work hands-on with LLMs, RAG pipelines, and AI agents, helping the team rapidly test hypotheses, build proofs of concept (PoCs), and deploy pilot systems in real operational contexts.

Key Responsibilities

• Prototype and evaluate foundation and multimodal models (e.g., GPT-4/5, Claude, Gemini, Llama 3, Mistral).
• Implement retrieval-augmented generation (RAG) workflows using vector databases (FAISS, Pinecone, Weaviate).
• Fine-tune or adapt models using LoRA and PEFT techniques for airport-specific data.
• Explore agentic AI tools (e.g., LangChain, AutoGen, CrewAI, LangGraph) to automate operational tasks.
• Build lightweight GenAI microservices with Python, FastAPI, and Docker for PoC deployment.
• Work with cloud platforms (AWS, GCP) for rapid model hosting and experimentation.
• Collaborate with data scientists and operations teams to test solutions in real-world settings.
• Document and share results, experiments, and learnings for future scalability.

Qualifications

• Bachelors or Masters degree in Computer Science, Machine Learning, or related fields.
• 2 - 5 years of experience in ML / GenAI development or applied research.
• Proficiency in Python, PyTorch, and Transformers.
• Hands-on experience with LLM APIs, LangChain, or LlamaIndex.
• Hands-on experience with cloud ML platforms (AWS Sagemaker, Bedrock, GCP Vertex AI).
• Comfortable with rapid prototyping, experimentation, and iterative design.

Nice-to-have:

• Exposure to multimodal or agentic AI systems.
• Understanding of prompt design, evaluation metrics, or hallucination detection.