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For Companies At a Glance
- Tasks: Build and deploy cutting-edge AI systems that transform businesses globally.
- Company: Join a forward-thinking tech company focused on real-world AI applications.
- Benefits: Competitive pay, hybrid work model, and the chance to shape AI's future.
- Other info: Collaborative environment with opportunities for professional growth and innovation.
- Why this job: Make a real impact by developing AI solutions that enhance decision-making and automate workflows.
- 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.
Data Marketing 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 Data Marketing 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 put in a good word for you.
✨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 coding challenges and be ready to discuss your past projects in detail, especially how you've deployed real-world AI solutions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Data Marketing 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 work with LLMs, AI agents, and any relevant frameworks like LangChain or TensorFlow. We want to see how you’ve built real-world AI systems!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and how your experience aligns with our mission at StudySmarter. Tell us about specific projects where you've taken AI from concept to production – we love hearing about your journey!
Showcase Your Projects: If you’ve got a portfolio or GitHub with projects related to AI, don’t hold back! Include links in your application. We’re keen to see your hands-on work with AI systems and how you’ve tackled complex problems in the past.
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 this exciting opportunity. Plus, it shows you’re serious about 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 your previous roles. Highlight instances where you've built scalable AI systems or automated workflows, and be ready to explain the impact your work had on the business.
✨Get Familiar with the Company’s AI Vision
Research the company’s current AI initiatives and understand their goals for AI transformation. This will help you align your answers with their vision and demonstrate that you're genuinely interested in contributing to their mission.
✨Ask Insightful Questions
Prepare thoughtful questions about the role and the team you'll be working with. Inquire about their approach to MLOps, production deployment, and how they measure success in their AI projects. This shows your enthusiasm and helps you gauge if the company is the right fit for you.