Senior AIML Research Engineer
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Job Summary
Role: Senior AI/ML Research Engineer
Location: London 5 days onsite
Start Date: July 2026
End Date: 31st December 2026
Daily Rate: Inside IR35
Payroll provider Rockford Payroll Info for Contingent Workers Rockford Pay
This is an exciting opportunity to join Deloitte Operations for an engagement with one of our clients.
The Role
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 developmentfrom 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
Bachelors Masters 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.
Advanced programming skills (Python preferred) with experience in frameworks and tools such as JavaScript Kafka and reactive systems.
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).
Front-end development (React) or backend development (.NET/C#).
Commercial awareness and understanding of business value delivery.
Required Skills:
Qualification Bachelors Masters 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. Advanced programming skills (Python preferred) with experience in frameworks and tools such as JavaScript Kafka and reactive systems. 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.
