At a Glance
- Tasks: Design and build AI agents and workflows using cutting-edge LLM technology.
- Company: Join a leading AI company focused on real-world impact.
- Benefits: Competitive daily rate, fully remote work, and high ownership opportunities.
- Other info: Fast-paced environment with significant career growth potential.
- Why this job: Shape the future of AI with live systems that make a difference.
- Qualifications: Strong Python skills and experience deploying LLM-powered systems.
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 - Fully Remote employer: Russell Tobin
Join a forward-thinking company that prioritises innovation and real-world impact in the AI sector. With a fully remote work model, you will enjoy a flexible work culture that fosters collaboration and creativity, while also benefiting from competitive rates and opportunities for professional growth. This role offers the chance to work on live AI systems, ensuring your contributions are both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Fully Remote
✨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 measurable impacts.
✨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 build reliable systems, 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 looking for candidates who are ready to ship and make an impact in the AI world.
We think you need these skills to ace Machine Learning Engineer - Fully 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 hold back!
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 you’re keen on joining our team at StudySmarter!
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 you’ll likely be asked to discuss how you've used these in real-world applications.
✨Showcase Your Projects
Prepare to talk about specific projects where you’ve built and deployed AI systems. Highlight the impact these projects had, focusing on measurable outcomes. This will demonstrate your ability to deliver value, which is crucial for this role.
✨Understand the Business Impact
Be ready to discuss how your work in AI can drive business transformation. Think about examples where your AI solutions have improved efficiency or decision-making processes. This shows that you’re not just a techie but also understand the bigger picture.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s AI initiatives and how they measure success. This not only shows your interest but also gives you a chance to assess if the company aligns with your career goals and values.
