Data Scientist

We are seeking a Data Scientist to lead the integration of Generative AI and Agentic Workflows into our global projects. From automating complex engineering compliance to enhancing digital twins with natural language interfaces, your work will directly contribute to more sustainable and efficient infrastructure worldwide.

Your Impactful Role 

• Architecting the Future: Lead the end-to-end development and deployment of AI/ML projects, ensuring they solve real-world engineering and consultancy challenges. 

• Agentic Innovation: Design and implement Agentic AI architectures (using LangChain, Lang Graph, etc.) to automate complex reasoning tasks across technical documentation and project management. 

• From Vision to Reality: Rapidly develop Proof of Concepts (PoCs) and transition them into high-availability, enterprise-grade applications hosted on Azure. 

• Connected Thinking: Work alongside structural engineers, environmental consultants, and digital architects to integrate AI/ML into the wider ecosystem. 

• Strategic Growth: Contribute to the scale-up of AI solutions, ensuring cost-optimized deployment (LlmOps) and alignment with our commitment to ethical & responsible AI. 

Technical Excellence You Bring 

1. Generative AI & NLP Specialization 

• NLP Core: 5+ years of experience in working with NLP problems and 2+ years of experience in working with LLM. 

• Expertise in LLMs: Proven experience fine-tuning and deploying LLM models (GPT, Llama 3, Falcon) and proprietary models via Azure AI Foundry. 

• Agentic Architectures: Hands-on experience with agentic AI orchestration design patterns with building systems using LangChain, Crew AI, or Llama Index.  

• Advanced Retrieval: Mastery of RAG (Retrieval Augmented Generation), RAG Fusion, and Chain-of-Thought prompting to extract insights from massive technical datasets. 

• Foundational NLP: Deep understanding of Transformers (BERT, GPT), NLU, and NLG principles. 

2. Engineering & Machine Learning Mastery 

• ML Core: 5+ years of experience with algorithms including XGBoost, Random Forest, and advanced regression models/time series models. 

• Software Craftsmanship: Proficiency in Python with a focus on clean code, design patterns, and scalable architecture. Prior Exposure to end-to-end software development in enterprise environment. 

• Deep Learning: Practical experience with PyTorch or Keras for computationally intensive modelling. 

3. Data & Cloud Infrastructure 

• Azure Ecosystem: Strong track record of deploying models within Azure ML and managing the full ML lifecycle. 

• Modern Data Stack: Experience with Vector Databases (Pinecone, Milvus, or PgVector) and Graph Databases to support complex data relationships. 

• Operational Excellence: Knowledge of LlmOps, Docker, and Kubernetes to ensure model reliability and cost-efficiency. 

Desired Attributes 

• Collaborative Mindset: You thrive in cross-functional teams and can translate "AI-speak" into clear business value for non-technical stakeholders. 

• Sustainability Focus: An interest in how AI can drive better social outcomes and carbon reduction in infrastructure. 

• Leadership Behaviour: Comfortable taking additional challenges and excellent communication ability. 

• Agile Advocate: Comfortable working in fast-paced, iterative Agile environments.