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For Companies At a Glance
- Tasks: Design and deploy intelligent AI systems that automate workflows and enhance decision-making.
- Company: Join a global leader in AI innovation with a production-first engineering culture.
- Benefits: Competitive contract rate, hybrid work model, and the chance to shape future AI technologies.
- Other info: Collaborate with top engineers and data teams to drive enterprise AI transformation.
- Why this job: Make a real impact by building scalable AI systems used worldwide.
- Qualifications: Experience with LLMs, AI systems, and strong programming skills in Python.
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.
Marketing Data Scientist in City of London employer: Russell Tobin
Contact Detail:
Russell Tobin Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Marketing Data Scientist in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and AI systems. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining your past projects and how they relate to the role you're applying for. Confidence is key!
✨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 genuinely interested in joining our team.
We think you need these skills to ace Marketing Data Scientist in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your experience with LLMs, AI systems, and any relevant frameworks like LangChain or TensorFlow. We want to see how you can bring your unique expertise to our team!
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 perfect fit for this role. Don’t forget to mention specific projects where you've deployed real-world AI systems – we love seeing practical examples!
Showcase Your Projects: If you've worked on any interesting AI projects, make sure to include them in your application. Whether it's building autonomous AI agents or developing RAG pipelines, we want to know what you've done and how it relates to the work we do at StudySmarter.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Russell Tobin
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs, GenAI, and agentic AI systems. Be ready to discuss your hands-on experience with frameworks like LangChain or PyTorch, as well as any real-world projects you've worked on that showcase your ability to take AI from concept to production.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex problems in previous roles. Think about times when you designed and deployed intelligent AI systems or automated workflows, and be ready to explain your thought process and the impact of your solutions.
✨Get Familiar with Their Tech Stack
Research the tools and technologies mentioned in the job description, such as RAG pipelines and cloud platforms like AWS or Azure. Being able to speak confidently about these technologies will show that you're not just a fit for the role but also genuinely interested in their work.
✨Ask Insightful Questions
Prepare some thoughtful questions to ask during the interview. This could be about their current AI projects, team dynamics, or how they measure success in their AI initiatives. It shows you're engaged and eager to contribute to their goals.