At a Glance
- Tasks: Design and build AI agents for real-world applications using cutting-edge technologies.
- Company: Join a leading AI firm focused on impactful solutions.
- Benefits: Competitive daily rate, hybrid work model, and opportunities for professional growth.
- Other info: Fast-paced environment with high ownership and visibility in projects.
- Why this job: Make a real impact by deploying live AI systems at scale.
- Qualifications: Strong Python skills and experience with LLM-powered systems required.
Location: London (Hybrid)
Contract: Outside IR35
Rate: £500–£550 per day (depending on interview outcome)
We’re looking for AI operators who ship — not experiment. This is an opportunity to join a major AI build focused on deploying real-world LLM and agentic systems at scale across both AI products and enterprise transformation initiatives. You’ll be working in a production-first environment where the emphasis is on building reliable, scalable AI systems that deliver measurable business impact.
What You’ll Be Working On
- Designing and building AI agents and agentic workflows powered by LLMs
- Developing systems using RAG, reasoning, planning, memory, and tool orchestration
- Building multi-step intelligent systems capable of real-world tool usage
- Working with MCP-style architectures (or equivalent) to structure context and improve interoperability
- Contributing to recommendation, classification, and forecasting systems using large-scale datasets
- Automating business workflows and decision-making processes through AI-driven solutions
What You’ll Be Doing
- Owning projects end-to-end from concept through to production deployment and iteration
- Building and deploying AI agents that operate reliably in production environments
- Integrating AI systems into APIs, products, and operational workflows
- Collaborating closely with engineering teams to ensure scalability, observability, and maintainability
- Making pragmatic decisions balancing model performance, latency, and cost efficiency
Core Requirements
- Strong Python skills with experience writing production-grade code
- Proven experience deploying LLM-powered systems into production environments
- Hands-on experience with LangChain, LangGraph, or equivalent orchestration frameworks
- Experience building AI agents and agentic workflows with tool usage and multi-step reasoning
- Strong understanding and implementation experience of RAG systems
- Familiarity with MCP/FastMCP/FastAPI or similar orchestration patterns
- Strong understanding of LLM trade-offs including hallucination mitigation, latency, and cost optimisation
- Experience deploying AI systems in cloud environments such as AWS, GCP, or Azure
- Working knowledge of SQL/data manipulation (Working knowledge of SQL or data manipulation is expected, but it is not a primary focus for this role.)
Strong signals include:
- Experience working on SaaS or B2B AI products or delivering AI-driven transformation within an organisation.
- A background in high-growth or scaling environments, where speed and pragmatism are critical.
- Clear evidence of systems that are actively used and delivering value, rather than experimental work.
Ideal Background
- Masters degree or higher in Computer Science, Mathematics, Engineering, or a related technical field
- Experience building and iterating on AI systems delivering measurable value
- Strong ownership mindset and ability to operate in fast-moving environments
- Product-focused approach with a bias toward delivering impact
Why This Role
- Work on live AI systems used at scale
- Join a well-supported AI engineering environment
- High ownership and visibility across products and operations
- Opportunity to shape enterprise AI adoption in a meaningful way
Machine Learning Engineer - Hybrid Remote employer: Russell Tobin
Join a forward-thinking company that prioritises innovation and real-world impact in the AI sector. With a hybrid work model based in London, you'll benefit from a collaborative culture that fosters professional growth and encourages ownership of projects from concept to deployment. Enjoy competitive rates and the opportunity to work on cutting-edge AI systems that are actively transforming businesses, all while being part of a supportive team dedicated to excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Hybrid Remote
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Prepare for those interviews by practising common questions and showcasing your projects. We recommend having a portfolio ready that highlights your experience with LLMs and AI systems — it’ll make you stand out!
✨Tip Number 3
Don’t shy away from asking insightful questions during interviews. Show us you’re genuinely interested in the role and the company’s AI initiatives. It’s a great way to demonstrate your knowledge and enthusiasm!
✨Tip Number 4
Apply through our website! We love seeing candidates who are proactive. Plus, it gives you a chance to showcase your skills and experience directly to us, making it easier for you to land that Machine Learning Engineer role.
We think you need these skills to ace Machine Learning Engineer - Hybrid Remote
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your Python skills, experience with LLMs, and any relevant projects you've worked on. We want to see how you can contribute to our AI build!
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 aligns with our mission at StudySmarter. Be specific about your experience with deploying AI systems and how you’ve made an impact in previous roles.
Showcase Your Projects:If you've worked on any AI projects, make sure to include them in your application. We love seeing real-world examples of your work, especially those that demonstrate your ability to build reliable, scalable systems. Don’t be shy—let us know what you’ve achieved!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. Plus, we’re excited to see what you bring to the table!
How to prepare for a job interview at Russell Tobin
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and LLMs. Brush up on your experience with LangChain and RAG systems, as these will likely come up during the interview.
✨Showcase Real-World Impact
Prepare to discuss specific projects where you've deployed AI systems that delivered measurable business impact. Highlight your ownership of these projects and how they contributed to the organisation's goals.
✨Be Ready for Practical Scenarios
Expect scenario-based questions where you’ll need to demonstrate your problem-solving skills. Think about how you would approach building and deploying AI agents in a production environment, balancing performance and cost.
✨Collaborate and Communicate
Since collaboration is key in this role, be prepared to discuss how you’ve worked with engineering teams in the past. Emphasise your ability to communicate technical concepts clearly and work effectively in a team setting.
