Deloitte
Senior AI/ML Research Engineer
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Contract Role: Senior AI/ML Research Engineer
Contract Location: London
Contract Duration: 6 months initially (with potential extension)
Contract Start Date: Immediate
Contract Classification: Inside IR35
Daily Rate Breakdown
- Traditional Daily Rate: £600
- Agreed Contract Rate (ACR): £462
- Equivalent Annual Salary: £120k + £14.5k holiday pay
Payroll Provider: Rockford Payroll Info for Contingent Workers – Rockford Pay
Overview
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.
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Essential Skills & Experience
- 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.
- 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.
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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.
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