At a Glance
- Tasks: Build and deploy cutting-edge AI systems that make a real-world impact.
- Company: Join a global leader in AI innovation with a collaborative culture.
- Benefits: Competitive pay, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement opportunities in a fast-paced environment.
- Why this job: Shape the future of AI and work on high-impact projects that matter.
- Qualifications: Experience with LLMs, AI systems, and strong programming skills required.
The predicted salary is between 80000 - 98000 £ per year.
Hybrid – London (3 days office - 2 days remote)
Rate: 500-550 Outside IR 35
Contract: 6 months initially
Build Production-Grade AI Systems at Scale
We’re looking for AI builders — not just experimenters. If you’ve deployed real-world LLMs, built autonomous AI agents, and engineered scalable AI systems that people actually use, this is the opportunity to shape the future of AI across a global organisation.
We’re building next-generation AI capabilities across both:
- AI-powered SaaS / B2B products
- Enterprise-wide AI transformation initiatives
You’ll work on high-impact systems that automate workflows, enhance decision-making, and deliver measurable business value at scale.
What You’ll Build
You’ll design and deploy intelligent AI systems powered by:
- Large Language Models (LLMs)
- Agentic AI frameworks
- Retrieval-Augmented Generation (RAG)
- Multi-agent orchestration
- Tool-using autonomous workflows
This is a hands-on engineering role focused on production delivery, scalability, reliability, and business impact.
Your Work Will Include
- Building AI agents with reasoning, planning, memory, and tool orchestration
- Developing advanced RAG pipelines and context-aware AI systems
- Designing MCP-style architectures and interoperable AI workflows
- Creating recommendation, forecasting, and classification models on large-scale datasets
- Automating complex business operations using AI-driven decision systems
- Integrating AI into APIs, enterprise platforms, and customer-facing products
- Optimising latency, inference performance, observability, and cost efficiency
What We’re Looking For
We want engineers and scientists who can take AI from concept to production.
Strong Experience In
- LLMs, GenAI, and Agentic AI systems
- LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks
- RAG pipelines and vector databases
- AI agents and multi-agent orchestration
- Python, PyTorch, TensorFlow, Scikit-learn
- Cloud AI platforms such as AWS, Azure, or GCP
- Production deployment, MLOps, and scalable AI infrastructure
- API integration and workflow automation
Bonus Points For
- MCP / Model Context Protocol experience
- Fine-tuning and evaluation frameworks
- Recommendation systems and forecasting models
- Real-world enterprise AI transformation experience
- Experience balancing model quality, latency, and operational cost
Why Join Us?
- Work on AI systems used at global scale
- Join a production-first AI engineering culture
- Build technology that directly impacts products, operations, and business strategy
- Collaborate with strong engineering, product, and data teams
- Influence how enterprise AI is designed and deployed across a global organisation
If you enjoy solving complex problems, deploying real AI systems, and building beyond prototypes, this role offers the opportunity to make a genuine impact.
AI Scientist in London employer: Russell Tobin
Join a forward-thinking organisation that prioritises innovation and collaboration in the heart of London. As an AI Scientist, you'll be part of a dynamic team dedicated to building impactful AI systems that drive real business value, all while enjoying a hybrid work model that promotes work-life balance. With ample opportunities for professional growth and a culture that values hands-on engineering, this is the perfect environment for those looking to make a meaningful contribution to the future of AI.
StudySmarter Expert Advice🤫
We think this is how you could land AI Scientist in 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 Russell Tobin 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 Russell Tobin.
✨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 Russell Tobin.
We think you need these skills to ace AI Scientist in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Russell Tobin, 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 Russell Tobin, 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 Russell Tobin’s attention and show the tangible impact of your work.
How to prepare for a job interview at Russell Tobin
✨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 Russell Tobin.
✨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 Russell Tobin.
✨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 Russell Tobin.
