AI/ML Engineer for Conversational AI and RAG in London

AI/ML Engineer for Conversational AI and RAG in London

London Full-Time 35000 - 45000 £ / year (est.) Home office (partial)
EBRD

At a Glance

  • Tasks: Support the development of AI applications like chatbots and RAG systems.
  • Company: Join a pioneering international organisation focused on innovation and inclusivity.
  • Benefits: Enjoy a hybrid workplace, competitive benefits, and a focus on employee wellbeing.
  • Other info: Embrace a culture of continuous improvement and responsible AI practices.
  • Why this job: Make a real impact in AI while collaborating with diverse experts.
  • Qualifications: Degree in a technical field and experience with Python required.

The predicted salary is between 35000 - 45000 £ per year.

The Analyst, AI/ML Engineer plays a supporting role in the development of AI/ML applications such as chatbots, conversational AI applications, and retrieval-augmented generation (RAG) systems. The role will involve day-to-day tasks such as application design and implementation, data preparation, conversational bot development, model testing, documentation, and pipeline support.

Working under the supervision of senior engineers, the Analyst follows established engineering standards and agile practices to ensure quality and consistency across the AI delivery lifecycle. Responsibilities include:

  • Assisting in building AI solutions using Azure AI Services, Prompt Flow, and Azure AI Search (Vector Store).
  • Writing clean, testable code and assisting in peer code reviews.
  • Supporting the setup of automated testing and observability within CI/CD pipelines.
  • Contributing to the validation and tuning of models to ensure performance and data quality, adhering to AI fairness and explainability principles.
  • Participating in the refinement of AI/ML user stories and contributing to backlog grooming, estimation, and agile ceremonies.
  • Supporting the delivery of small to medium AI features in coordination with MLOps and Product teams.
  • Contributing to the promotion of engineering best practices and responsible AI standards.
  • Supporting continuous improvement and innovation within the squad.
  • Conducting technical spikes for new initiatives, under guidance where required.
  • Assisting with the deployment of training and inference pipelines to shared development environments such as Azure ML and Prompt Flow.

Knowledge and Education

  • Holds a degree in Computer Science, Data Science, Engineering, Mathematics or a related technical discipline.
  • 2 years of experience working with Python.
  • Demonstrates foundational understanding of machine learning concepts, model lifecycle, and data processing principles.
  • Basic understanding of Software Development principles, including writing unit and integration tests.
  • Demonstrates problem-solving and analytical thinking skills.
  • Able to follow guidance and apply structured approaches to technical challenges.
  • Familiar with Agile ways of working and collaborative development practices (e.g. Scrum, Kanban).
  • Basic understanding of version control systems (e.g. Git) and collaborative tooling (e.g. GitHub, Jira, Confluence).
  • Effective written and verbal communication skills, including the ability to document work clearly.
  • Curious, proactive, and eager to learn in a hands-on engineering environment.
  • Demonstrates an awareness of responsible AI principles such as fairness, transparency, and explainability.
  • Able to work in a diverse, multicultural team setting and follow standard delivery processes.
  • Familiarity with containerisation using Docker is desirable.
  • Hands-on experience or academic exposure to Python for data science or AI/ML development.
  • Basic understanding of RESTful API design principles.
  • Familiar with model development workflows, including training, evaluation, and basic tuning.
  • Exposure to tools such as Azure ML, Prompt Flow, or similar cloud ML platforms.
  • Basic understanding of AI/ML application types such as chatbots, recommendation systems, or RAG.
  • Supports building and testing ML models, preparing datasets, and writing testable code.
  • Exposure to vector search, embeddings, or retrieval techniques is desirable.
  • Assists with basic ML pipeline configuration under guidance.
  • Ability to write clear technical documentation and maintain API specifications using Open API 3.0+
  • Basic understanding of System Design and Architecture.
  • Basic understanding of microservices architecture and distributed system design.
  • Familiarity with application authentication protocols (e.g. OAuth 2.0, JWT), and security best practices.

What is it like to work at the EBRD?

Our agile and innovative approach is what makes life at the EBRD a unique experience! You will be part of a pioneering and diverse international organisation, using your talents to make a real difference to people's lives and help shape the future of the regions we invest in.

At EBRD, our Values – Inclusiveness, Innovation, Trust, and Responsibility – are at the heart of how we work. We bring these to life through our Workplace Behaviours: listening well and speaking up, collaborating smartly, acting decisively with full commitment, and simplifying to amplify our impact. These principles shape our culture and define our success. We seek individuals who not only share these values but are also committed to embedding them in their daily work, fostering a positive and high-performing environment.

The EBRD Environment Provides You With

  • Varied, stimulating, and engaging work that gives you an opportunity to interact with a wide range of experts in the financial, political, public, and private sectors across the regions we invest in.
  • A working culture that embraces inclusion and celebrates diversity.
  • A hybrid workplace that offers flexibility to teams and individuals; based on trust, flexibility, and connectedness.
  • An environment that places sustainability, equality, and digital transformation at the heart of what we do.
  • A workplace that prioritises employee wellbeing and provides a comprehensive suite of competitive benefits.

Diversity is one of the Bank’s core values which are at the heart of everything it does. As such, the EBRD seeks to ensure that everyone is treated with respect and given equal opportunities and works in an inclusive environment. The EBRD encourages all qualified candidates who are nationals of the EBRD member countries to apply regardless of their racial, ethnic, religious and cultural background, gender, gender identity, sexual orientation, age, socio-economic background, or disability.

Please note, that due to the high volume of applications received, we regret to inform you that we are unable to provide detailed feedback to candidates who have not been shortlisted.

AI/ML Engineer for Conversational AI and RAG in London employer: EBRD

At EBRD, we pride ourselves on fostering a dynamic and inclusive work environment that champions innovation and collaboration. As an AI/ML Engineer in London, you will engage in meaningful projects that leverage cutting-edge technology while benefiting from a hybrid workplace that prioritises flexibility and employee wellbeing. With a strong commitment to professional growth and a culture that values diverse perspectives, EBRD is an exceptional employer for those looking to make a real impact in the field of AI.

EBRD

Contact Details:

EBRD Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI/ML Engineer for Conversational AI and RAG in London

Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to AI/ML. This gives potential employers a taste of what you can do and sets you apart from the crowd.

Tip Number 3

Prepare for interviews by practising common technical questions and coding challenges. Use platforms like LeetCode or HackerRank to sharpen your skills and boost your confidence before the big day.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!

We think you need these skills to ace AI/ML Engineer for Conversational AI and RAG in London

Python
Machine Learning Concepts
Data Processing Principles
Software Development Principles
Unit and Integration Testing
Agile Methodologies
Version Control Systems (Git)

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with AI/ML applications, especially in areas like chatbots and RAG systems. We want to see how your skills align with the role, so don’t hold back!

Show Off Your Coding Skills:Since writing clean, testable code is key for this position, include examples of your Python projects or any relevant coding experience. If you’ve contributed to peer code reviews, mention that too – it shows you’re a team player!

Demonstrate Your Understanding of Agile Practices:We love candidates who are familiar with Agile methodologies. Share any experiences you have with Scrum or Kanban, and how you’ve contributed to backlog grooming or agile ceremonies in past roles.

Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can’t wait to hear from you!

How to prepare for a job interview at EBRD

Know Your AI/ML Basics

Make sure you brush up on your foundational knowledge of machine learning concepts and the model lifecycle. Be ready to discuss how you've applied these principles in past projects, especially in relation to chatbots or RAG systems.

Showcase Your Coding Skills

Since writing clean, testable code is crucial for this role, be prepared to demonstrate your Python skills. You might be asked to solve a coding challenge or explain your approach to writing unit tests, so practice coding problems beforehand.

Familiarise Yourself with Agile Practices

Understanding Agile methodologies is key. Be ready to talk about your experience with Scrum or Kanban, and how you've contributed to backlog grooming or sprint planning in previous roles. This shows you're a team player who can adapt to their workflow.

Emphasise Your Curiosity and Learning Mindset

This role values curiosity and a proactive attitude. Share examples of how you've taken the initiative to learn new tools or technologies, like Azure AI Services or Docker, and how that has positively impacted your work or team.