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For Companies At a Glance
- Tasks: Design and build AI agents and workflows that deliver real-world impact.
- Company: Join a leading AI firm focused on scalable solutions.
- Benefits: Competitive daily rate, hybrid work model, and high visibility in projects.
- Other info: Fast-paced environment with opportunities for ownership and growth.
- Why this job: Shape the future of AI with live systems and meaningful enterprise impact.
- 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 in London employer: Russell Tobin
Contact Detail:
Russell Tobin Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Hybrid Remote in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and machine learning space on LinkedIn or at meetups. We can’t stress enough how important it is to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and AI agents. We love seeing real-world applications of your work, so make sure to highlight any measurable impact you've made.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and production-grade coding skills. We want to see you demonstrate your ability to deploy AI systems effectively, so practice coding challenges and system design questions.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for candidates who are ready to ship real-world AI solutions, just like you!
We think you need these skills to ace Machine Learning Engineer - Hybrid Remote in 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 Python prowess, 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. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any AI systems or projects, make sure to include them in your application. We’re interested in real-world applications, so share examples of how your work has delivered measurable impact. This is your time to brag a little!
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 don’t miss out on any important updates. Plus, we love seeing candidates who take that extra step!
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 LLM systems. Brush up on your experience with LangChain and RAG systems, as these will likely come up during technical discussions.
✨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, as this aligns perfectly with what they're looking for.
✨Be Ready for Problem-Solving Questions
Expect questions that assess your ability to make pragmatic decisions regarding model performance, latency, and cost efficiency. Think of examples where you had to balance these factors in a production environment and be ready to explain your thought process.
✨Collaborate and Communicate
Since collaboration is key in this role, prepare to discuss how you've worked closely with engineering teams in the past. Be ready to share examples of how you ensured scalability and maintainability in your projects, showcasing your teamwork skills.