Wood is a global leader in consulting and engineering, helping to unlock solutions to critical challenges in energy and materials markets. We provide consulting, projects and operations solutions in 45 countries, employing around 25,000 people. www.woodplc.com
Diversity Statement 
We are an equal opportunity employer that recognises the value of a diverse workforce. All suitably qualified applicants will receive consideration for employment on the basis of objective criteria and without regard to the following (which is a non-exhaustive list): race, colour, age, religion, gender, national origin, disability, sexual orientation, gender identity, protected veteran status, or other characteristics in accordance with the relevant governing laws.

Responsibilities:

1. Development

• Design, develop, and deploy end-to-end AI applications, including scalable and production-ready systems.
• Build and integrate RESTful APIs and microservices to expose AI functionalities.
• Implement data ingestion, extraction (including OCR), and preprocessing pipelines for structured and unstructured data (text, images, documents).
• Develop and maintain vector databases, embedding pipelines, and chunking strategies for efficient semantic retrieval.

2. Models & Fine-Tuning

• Build and optimize LLM-based solutions using Prompt Engineering, RAG architectures, and fine-tuning techniques.
• Develop and apply machine learning models (regression, classification, clustering) for predictive analytics.
• Work on computer vision and image processing models using tools such as OpenCV, OCR frameworks, and deep learning-based image models.
• Continuously improve model performance through evaluation, hyperparameter tuning, and feedback loops.

3. Research & Innovation

• Stay current with advancements in AI/ML, NLP, Computer Vision, and Generative AI ecosystems.
• Explore and experiment with new techniques in prompt engineering, RAG optimization, and LLM architectures.
• Propose innovative solutions to enhance automation, accuracy, and scalability of AI systems.

4. Use Case Development

• Collaborate with stakeholders to understand business requirements and translate them into AI solutions.
• Design and develop chatbots, virtual assistants, and domain-specific AI applications.
• Create tailored AI workflows for content generation, document processing, and intelligent automation.

5. Quality Assurance

• Implement testing and validation frameworks to ensure AI model reliability and accuracy.
• Analyse outputs for relevance, coherence, and performance, and refine models/prompts accordingly.
• Establish monitoring mechanisms for production AI systems to ensure consistent performance.
• Document processes, workflows, and best practices for maintainability and knowledge sharing.

Qualifications:

Qualifications

• Bachelor’s or master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field (Ph.D. is an advantage).
• 3+ years of experience in AI/ML, Natural Language Processing, or related domains.
• Strong proficiency in Python and experience with AI/ML and NLP libraries (e.g., Hugging Face, spaCy, OpenCV).
• Proven understanding of Large Language Models (LLMs) such as GPT, BERT, and their real-world applications.
• Hands-on experience in Prompt Engineering, RAG architectures, chatbot development, and AI system integration.
• Experience with machine learning algorithms (regression, classification, clustering) and model evaluation techniques.
• Familiarity with image processing and computer vision techniques, including OCR and deep learning-based image models.
• Experience in designing and deploying APIs and scalable AI solutions.
• Strong analytical, problem-solving, and communication skills with the ability to work in cross-functional teams.

Knowledge, Skills & Experience

• Experience working with cloud platforms (AWS, Azure, or Google Cloud) and AI/ML services.
• Proficiency in machine learning and deep learning frameworks (TensorFlow, PyTorch).
• Hands-on knowledge of vector databases, embeddings, chunking strategies, and semantic search systems.
• Understanding of advanced AI techniques such as reinforcement learning and model fine-tuning.
• Experience in building end-to-end AI systems, including data pipelines, model deployment, and monitoring.
• Familiarity with UX principles and the ability to design AI systems aligned with user needs and behaviours.
• Awareness of AI ethics, model bias, and responsible AI practices.

Personal Attributes

• Demonstrates a strong commitment to continuous learning and skill development in emerging AI technologies.
• Detail-oriented, diligent, and dependable in following established processes and standards.
• Professional demeanour with strong interpersonal and collaboration skills.
• Ability to work independently, troubleshoot issues, and deliver solutions proactively.
• Highly organized with effective time management and communication abilities.
• Capable of working under timelines and delivery targets in a dynamic environment.
• Strong team player with the ability to work across multidisciplinary teams with minimal supervision.
• Acts as a role model by demonstrating organizational values and professional behaviours.