Manager, AI Engineer, AI & Data, AI Scaling & Transformation

Overview

In this AI/ML Engineer role, you will deliver end-to-end AI solutions for client projects within Deloitte’s AI&D operating unit. You’ll work with cross-functional teams to turn business needs into scalable ML-enabled platforms while staying ahead of AI trends. You’ll manage client relationships, deliver tangible data-driven outcomes, and contribute to multi-disciplinary engagements across industries. The role is embedded in a collaborative, high-growth environment that values innovation and impact.

Pay / Benefits

• Hybrid working in Manchester
• Flexible working arrangements
• Training and development opportunities
• Wellbeing support
• Supportive culture emphasizing inclusion and collaboration

Responsibilities

• Collaborate with client stakeholders and internal teams to translate business requirements into AI solutions
• Design, build, and deploy end-to-end AI pipelines (data acquisition, preprocessing, feature engineering, model training, deployment)
• Develop and maintain AI/ML models (prediction, classification, automation, insight generation)
• Create scalable data pipelines and data models to support analytics and AI use cases
• Stay updated on AI advancements and evaluate new technologies
• Optimize data processing, storage, and model performance for scalability and efficiency
• Deliver solutions in agile delivery environments and manage client stakeholder relationships

Key requirements

• Hands-on experience in developing and deploying AI solutions
• Experience building data pipelines with structured and unstructured data
• Experience with MLOps, deployment, monitoring, and governance
• Experience working in Agile environments
• Strong programming skills in Python, SQL, or similar
• Proficiency with TensorFlow, PyTorch, scikit-learn; familiarity with Langchain desirable
• Solid understanding of ML algorithms, deep learning, and statistical modelling
• Experience with cloud platforms (AWS, Azure, GCP) and their AI services
• Data engineering proficiency with SQL and big data tech (Spark, Hadoop)
• Experience with ETL, data pipelines, and automated workflows
• Data governance, security, privacy, metadata management, data quality, lineage
• Knowledge of distributed computing (parallel processing, streaming, batch orchestration)

• Analytical and problem-solving mindset
• Strong communication and stakeholder management
• Team collaboration and adaptability
• Python
• SQL
• TensorFlow

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