Senior Consultant/Manager, AI/ML Engineer, AI Scaling and Transformation, Engineering, AI Data, Technology Transformation

Role overview

Responsibilities

• check_circle Work with client stakeholders, product owners and Deloitte teams to understand business challenges and translate them into practical AI/ML solution designs.
• check_circle Design, build, test and deploy machine learning models, Generative AI components, data pipelines and analytics solutions that are robust, scalable and maintainable.
• check_circle Take ownership of technical deliverables or workstreams, ensuring engineering outputs are aligned to agreed requirements, delivery plans and quality standards.
• check_circle Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.
• check_circle Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.
• check_circle Apply responsible AI, security, privacy and governance considerations throughout the development lifecycle.
• check_circle Contribute to the development of junior team members by sharing engineering knowledge, reviewing outputs and supporting a culture of continuous improvement.

Basic qualifications

• Degree or equivalent experience in Computer Science, Data Engineering, Mathematics, Artificial Intelligence, Machine Learning or a related discipline.
• Hands-on experience designing, developing and deploying AI, machine learning or Generative AI solutions in a consulting, commercial or technology delivery environment.
• Experience working with business and technical stakeholders to understand requirements, shape solution options and deliver measurable outcomes.
• Proven ability to own technical deliverables or workstreams, manage delivery priorities and communicate progress clearly to project teams and stakeholders.
• Experience working in data-intensive, regulated or complex enterprise environments is advantageous.

Preferred qualifications

• Strong proficiency in Python or another modern programming language used for AI/ML development, with practical experience across model development, testing and deployment.
• Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent.
• Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations.
• Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation.
• Experience using cloud platforms and cloud-native AI/ML services, such as Azure, AWS or GCP, to build and deploy scalable solutions.
• Strong communication and collaboration skills, with the ability to explain technical concepts to both engineering teams and non-technical stakeholders.

About the company