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About the Role

The Senior AI/ML Research Engineer will be a key member of the GenAI team, responsible for designing, developing, and deploying scalable AI/ML solutions. 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 exploration and experimentation through to deployment, monitoring, and optimisation, working closely with cross-functional teams.

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.

Requirements

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.
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

Skills

Python
JavaScript
Kafka
Reactive systems
Azure
Kubernetes
CI/CD
ADLS
Spark
Databricks
SQL
NoSQL
PySpark
Terraform
Helm
LangChain
Azure OpenAI
RAG
Text-to-SQL
Linux
Bash
PowerShell
React
.NET
C#

Location

London

Work Type

Contract
Inside IR35

Experience Level

Senior
10+ years

Education Level

Bachelor's
Master's
PhD

Salary/Compensations

£120k + £14.5k holiday pay

Benefits

6 months initially (with potential extension)
Immediate start