Artificial Intelligence / Machine Learning Engineer
Duration: 5 months renewable
Location: London
Start date: ASAP
Payrate: £700.00 Inside IR35
This position sits within a Data & AI organisation delivering scalable AI/ML solutions, with a strong focus on enterprise quality, reliability, and scalability. The Senior AI/ML Research Engineer will contribute to the development of modern machine learning systems in an environment where cloud-based development, data platforms, and advanced AI tooling are central to delivery.
The Senior AI/ML Research Engineer will design, develop, and deploy scalable AI/ML solutions from experimentation through to production. This role is central to building reusable machine learning architectures, supporting automation across the AI/ML lifecycle, and helping translate business needs into technical solutions.
- 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.
- 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.
- 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.
- 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.
- 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.