At a Glance
- Tasks: Design, build, and deploy cutting-edge GenAI applications using Python.
- Company: Join a forward-thinking tech company focused on innovative AI solutions.
- Benefits: Competitive pay, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on end-to-end system development.
- Why this job: Make a real impact by bringing GenAI ideas to life in production systems.
- Qualifications: Experience in building GenAI applications and strong Python skills required.
The predicted salary is between 80000 - 98000 £ per year.
Im 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 youll design, build, deploy, and monitor GenAI applications that integrate LLMs as part of a wider system.
Youll 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
Were 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 youve built and shipped GenAI applications and want to work on high-impact, enterprise-scale projects, please apply.
Senior Machine Learning Engineer - GenAI, LLM, RAG in City of London employer: Puritas Group
Join a forward-thinking company that values innovation and collaboration, where as a Senior Machine Learning Engineer, you'll have the opportunity to work on cutting-edge GenAI applications in a dynamic environment. With a strong emphasis on employee growth, we offer continuous learning opportunities and a supportive culture that encourages creativity and teamwork. Located in a vibrant tech hub, our workplace fosters a balance between professional development and personal well-being, making it an excellent choice for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer - GenAI, LLM, RAG in City of London
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Puritas Group before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like Puritas Group.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Puritas Group.
We think you need these skills to ace Senior Machine Learning Engineer - GenAI, LLM, RAG in City of London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Puritas Group, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Puritas Group, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Puritas Group’s attention and show the tangible impact of your work.
How to prepare for a job interview at Puritas Group
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Puritas Group.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Puritas Group.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Puritas Group.
