At a Glance
- Tasks: Build and optimise AI solutions using cutting-edge technologies and frameworks.
- Company: Join EPAM, a leading tech company in London with a hybrid work culture.
- Benefits: Enjoy competitive pay, health coverage, and perks like free lunches and social events.
- Other info: Great opportunities for learning and career growth in a dynamic environment.
- Why this job: Make a real impact in AI while working on innovative projects with a talented team.
- Qualifications: Strong Python skills and experience with API development and AI frameworks.
The predicted salary is between 60000 - 80000 £ per year.
We're looking for a Machine Learning Engineer to join EPAM in London, United Kingdom, in a hybrid working mode. You will contribute to an enterprise AI program for one of our clients by building and surfacing MCP Servers and Tools via the internal MCP Gateway and implementing evaluation mechanisms for large language models and agent-based systems. This is a highly technical role combining backend engineering, AI architecture, and enterprise integration to deliver scalable AI solutions.
As an AI Engineer, you will work on intelligent enterprise enablement through Model Context Protocol (MCP) integrations and advanced agent frameworks. The role involves API development with FastAPI, deployment of containerized systems, and implementing large language model (LLM) strategies such as prompt engineering and RAG (Retrieval-Augmented Generation). The successful candidate will operate in a Classic Agile environment to design, develop, and optimize next-generation enterprise AI capabilities.
Responsibilities- Build and surface MCP Servers and Tools using the internal MCP Gateway
- Develop APIs and service endpoints with FastAPI for MCP integrations
- Implement agent and LLM frameworks (e.g., LangChain, LangGraph) to enable sophisticated AI workflows
- Apply prompt engineering strategies and build RAG-based architecture for enhanced response accuracy
- Automate quality controls and develop evaluation systems for LLM reliability and performance
- Containerize and orchestrate AI services using Kubernetes for scalable deployment
- Collaborate cross-functionally with product, QA, and architecture teams to ensure secure, enterprise-grade solutions
- Maintain documentation for MCP integrations, testing pipelines, and workflow standards
- Integrate CI/CD practices to streamline deployment and testing processes
- Strong programming experience in Python for backend development and automation
- Expertise in REST API development using FastAPI for production-scale services
- Familiarity with Model Context Protocol (MCP) standards, server/client patterns
- Working knowledge of LLM/agent frameworks such as LangChain or LangGraph
- Understanding of containerization and orchestration tools like Kubernetes
- Ability to implement prompt engineering principles and RAG-based solutions
- Solid grasp of Agile delivery models, CI/CD workflows, and secure coding practices
- Excellent problem-solving and cross-team communication skills
- Experience with observability and monitoring tools for AI-driven workloads
- Familiarity with vector databases for semantic search and retrieval
- Knowledge of cloud platforms (AWS, GCP, Azure) and GPU-accelerated compute
- Background designing evaluation frameworks for AI model performance
- Exposure to large-scale AI deployment in enterprise environments
- EPAM Employee Stock Purchase Plan (ESPP)
- Protection benefits including life assurance, income protection and critical illness cover
- Private medical insurance and dental care
- Employee Assistance Program
- Cyclescheme, Techscheme and season ticket loans
- Various perks such as free Wednesday lunch in-office, on-site massages and regular social events
- Learning and development opportunities including in-house training and coaching, professional certifications, and courses
- If otherwise eligible, participation in the discretionary annual bonus program
- If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program
Machine Learning Engineer in London employer: EPAM Systems
EPAM is an exceptional employer for Machine Learning Engineers, offering a dynamic hybrid work environment in London that fosters innovation and collaboration. With a strong focus on employee growth through in-house training, professional certifications, and a supportive work culture, EPAM ensures that its team members are well-equipped to tackle cutting-edge AI challenges while enjoying unique perks like free lunches and on-site massages.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and machine learning. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for technical interviews by practicing coding challenges and system design questions. Use platforms like LeetCode or HackerRank to sharpen your skills and boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with Python, FastAPI, and any relevant AI frameworks. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for our team. Keep it engaging and relevant to the job description.
Showcase Your Projects:If you've worked on any projects related to LLMs, containerization, or API development, make sure to mention them. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at EPAM Systems
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills, especially for backend development. Familiarise yourself with FastAPI and how to develop REST APIs, as these are crucial for the role. Being able to discuss your experience with containerization tools like Kubernetes will also give you an edge.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous projects, particularly those involving AI architecture or LLM frameworks. Use the STAR method (Situation, Task, Action, Result) to structure your answers and demonstrate your problem-solving abilities effectively.
✨Understand Agile Methodologies
Since this role operates in a Classic Agile environment, be ready to talk about your experience with Agile delivery models and CI/CD workflows. Highlight any past experiences where you collaborated cross-functionally with teams to deliver secure, enterprise-grade solutions.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's AI initiatives and the specific projects you'll be working on. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values, especially regarding learning and development opportunities.
