Senior AI/ML Research Engineer in London

This is an exciting opportunity to join Deloitte Operations for an engagement with one of our clients.

The Senior AI/ML Research Engineer will be a key member of the GenAI team within the Data & AI organisation, responsible for designing, developing, and deploying scalable AI/ML solutions across multiple business areas. The role focuses on delivering production-grade machine learning systems while ensuring alignment with enterprise quality, reliability, and scalability standards. The successful candidate will lead end-to-end AI/ML solution development—from data exploration and experimentation through to deployment, monitoring, and continuous optimisation. They will work closely with cross-functional teams including data engineering, infrastructure, DevOps, and product management to translate business needs into robust, reusable machine learning architectures.

Key Responsibilities

• Design and deploy large-scale machine learning systems into production using modern engineering practices and tools.
• Build and maintain core ML infrastructure, including pipelines for feature engineering, model training, evaluation, deployment, and monitoring.
• Automate the full AI/ML lifecycle, covering data ingestion, experimentation, tuning, and visualisation.
• Collaborate with product teams to convert business requirements into scalable, reusable ML solutions.
• Partner with DevOps and infrastructure teams to improve deployment velocity, CI/CD processes, and reliability of data pipelines.
• Contribute to innovation by staying up to date with emerging AI/ML technologies and best practices.
• Support knowledge sharing and community initiatives across the organisation.

Experience & Skills Required

Qualification

• Bachelor’s, Master’s, or PhD in a relevant discipline (Engineering, Computer Science, Statistics, or related fields).
• 10+ years of experience in software development and machine learning engineering.

Core Technical Skills

• Strong expertise in designing large-scale machine learning systems and architectures.
• Extensive experience with cloud-based development, particularly on Azure, including AI/ML services and data platforms.
• Proven experience with Kubernetes for application deployment, scaling, and monitoring.
• Strong background in CI/CD pipeline design, automation, and maintenance.
• Hands-on experience with data engineering tools and storage solutions (e.g., ADLS, Spark, Databricks, SQL/NoSQL databases).
• Experience with distributed computing and big data processing frameworks such as PySpark.
• Knowledge of infrastructure-as-code tools such as Terraform and Helm.

Advanced / Specialist Expertise

• Experience building and deploying GenAI solutions using frameworks such as LangChain and Azure OpenAI.
• Development of enterprise-grade RAG (Retrieval-Augmented Generation) systems, including context engineering and multimodal data pipelines.
• Design and deployment of autonomous multi-agent systems using modern orchestration frameworks and evaluation approaches.
• Experience delivering Text-to-SQL solutions and natural language interfaces for structured data environments.

Additional Skills

• Strong understanding of data processing, cleansing, and handling large structured and unstructured datasets.
• Solid foundation in Linux, scripting (Bash/PowerShell), and networking fundamentals.
• Excellent communication skills with the ability to translate complex technical concepts into business terms.
• Experience working in agile, cross-functional, and globally distributed teams.
• Continuous learning mindset with a focus on emerging technologies and innovation.

Nice-to-Have

• Experience with AWS or GCP ML platforms (e.g., SageMaker, Vertex AI).
• Commercial awareness and understanding of business value delivery.