At a Glance
- Tasks: Build and deploy cutting-edge GenAI applications from concept to production.
- Company: Join a major enterprise AI transformation programme in Central London.
- Benefits: Competitive salary, flexible work arrangements, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on full-stack ML engineering.
- Why this job: Make a real impact by working on high-scale, innovative AI projects.
- Qualifications: Hands-on experience with GenAI applications and strong Python skills required.
The predicted salary is between 60000 - 80000 € per year.
Supporting a major enterprise AI transformation programme.
12 month contract Inside IR35, 2 days per week onsite - Central London.
I’m looking for Machine Learning Engineers (and Senior Data Scientists with strong engineering capability) who have real, hands‑on experience building GenAI applications end‑to‑end. Not just prototypes, but production systems.
This is a full‑stack ML Engineering role where you’ll design, build, deploy, and monitor GenAI applications that integrate LLMs as part of a wider system.
You’ll be working on:
- Building production‑grade GenAI applications using Python
- Developing LLM‑powered systems with LangChain, LangSmith, and modern Python libraries
- Designing and implementing RAG pipelines, vector stores, and retrieval logic
- Building agentic workflows, tool‑calling, and multi‑step reasoning systems
- Implementing guardrails, safety layers, and controls
- Designing monitoring for latency, drift, hallucinations, cost, and safety signals
- Integrating LLMs into broader application architectures (APIs, services, orchestration)
- Working across the full lifecycle: data prep → modelling → evaluation → deployment → observability
We’re looking for people who have:
- Delivered real GenAI applications into production, not just PoCs
- Strong Python engineering skills
- Experience with LangChain, LangSmith, LlamaIndex, or similar frameworks
- Deep understanding of LLM behaviour, prompting, evaluation, and optimisation
- Experience building monitoring, logging, and guardrail frameworks
- Ability to work across the stack: data, model, application, and infrastructure
- Strong communication skills and ability to work with product, engineering, and business teams
This is ideal for ML Engineers who love building end‑to‑end systems, not just models. People who can take a GenAI idea from concept to production and own the full lifecycle. If you’ve built and shipped GenAI applications and want to work on high‑impact, enterprise‑scale projects, please apply.
Machine Learning Engineer employer: Puritas Group
As a Machine Learning Engineer at our company, you will be part of a dynamic team driving a major enterprise AI transformation in the heart of Central London. We pride ourselves on fostering a collaborative work culture that encourages innovation and professional growth, offering opportunities to work on cutting-edge GenAI applications while enjoying a flexible work environment. With a focus on employee development and a commitment to impactful projects, we provide a unique platform for you to advance your career in a thriving tech landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and machine learning space. Attend meetups, webinars, or conferences where you can chat with industry folks. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your GenAI projects. Include links to GitHub repos or live demos of your applications. This is your chance to demonstrate your hands-on experience and make a lasting impression.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Python, LangChain, and building production systems. Practice explaining complex concepts in simple terms – communication is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented Machine Learning Engineers. Make sure your application stands out by tailoring it to highlight your end-to-end project experience and passion for GenAI.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show Off Your Experience:Make sure to highlight your hands-on experience with building GenAI applications. We want to see real examples of production systems you've worked on, not just prototypes. This is your chance to shine!
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific skills and experiences mentioned in the job description. We love seeing how you fit into our vision.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate straightforward communication, so make sure your skills and experiences are easy to find and understand.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to track your application and get back to you quickly!
How to prepare for a job interview at Puritas Group
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and frameworks like LangChain and LangSmith. Brush up on your experience with building production-grade GenAI applications, as this will be a key focus during the interview.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built end-to-end GenAI applications. Be ready to explain the challenges you faced, how you overcame them, and the impact of your work. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Full Lifecycle
Familiarise yourself with the entire machine learning lifecycle from data preparation to deployment and observability. Be prepared to discuss how you’ve implemented monitoring and guardrails in your previous projects, as this shows your attention to detail and commitment to quality.
✨Communicate Effectively
Strong communication skills are essential for this role. Practice explaining complex technical concepts in simple terms, as you’ll need to collaborate with product, engineering, and business teams. Being able to articulate your ideas clearly can set you apart from other candidates.
