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 salary, health insurance, stock options, and fun perks like free lunches.
- Other info: Great opportunities for learning, development, 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, experience with FastAPI, and knowledge of AI frameworks required.
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
- Competitive group pension plan
- 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 employer: EPAM Systems, Inc.
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, EPAM provides extensive learning and development opportunities, competitive benefits including private medical insurance and a generous pension plan, and a vibrant work culture enriched by regular social events and unique perks like free lunches and on-site massages. Join us to be part of cutting-edge AI projects while enjoying a supportive atmosphere that values your contributions and career advancement.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. We all know that sometimes it’s not just what you know, but who you know that can help you land that Machine Learning Engineer role.
✨Show Off Your Skills
Don’t just tell them what you can do; show them! Create a portfolio of projects that highlight your expertise in Python, FastAPI, and LLM frameworks. We recommend sharing your work on platforms like GitHub to give potential employers a taste of your coding chops.
✨Ace the Interview
Prepare for those technical interviews by brushing up on your problem-solving skills and understanding of Agile methodologies. We suggest practicing common interview questions related to AI architecture and containerization. Remember, confidence is key!
✨Apply Through Our Website
When you find a job that excites you, 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 genuinely interested in joining our team at EPAM.
We think you need these skills to ace Machine Learning Engineer
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 personal – we love to see your personality!
Showcase Your Projects:If you've worked on any projects related to LLMs or containerization, make sure to mention them! We’re keen to see real examples of your work, so don’t hold back on sharing your achievements and what you learned.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our awesome team at StudySmarter!
How to prepare for a job interview at EPAM Systems, Inc.
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and get comfortable with FastAPI. Be ready to discuss your experience with REST API development and how you've tackled backend challenges in the past. The more specific examples you can provide, the better!
✨Understand MCP and LLM Frameworks
Familiarise yourself with Model Context Protocol (MCP) standards and frameworks like LangChain or LangGraph. Be prepared to explain how you've implemented these in previous projects and how they can enhance AI workflows.
✨Showcase Your Agile Experience
Since this role operates in a Classic Agile environment, be ready to talk about your experience with Agile methodologies. Share examples of how you've collaborated with cross-functional teams and contributed to CI/CD practices in your past roles.
✨Ask Insightful Questions
Prepare some 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 it's the right fit for you.
