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- Tasks: Design and build advanced AI systems that operate in real environments.
- Company: Exciting AI company pushing the boundaries of technology.
- Benefits: Competitive salary, flexible work options, and opportunities for growth.
- Why this job: Join a team creating innovative solutions that make a real-world impact.
- Qualifications: Experience with AI systems and strong software engineering skills required.
- Other info: Dynamic work environment with a focus on collaboration and creativity.
The predicted salary is between 60000 - 80000 £ per year.
We’re working with a well-funded AI company building systems that go far beyond standard LLM applications. This isn’t about prompt → response or simple RAG pipelines. The focus is on agent-driven systems that operate in real environments; taking actions, orchestrating tools, and producing outputs across complex workflows.
What you’ll be doing:
- Designing and building agentic / multi-agent systems in production
- Working on reasoning, memory, and tool orchestration
- Integrating models into real systems with live state, feedback loops, and execution layers
- Collaborating closely with platform and product teams to ship end-to-end AI functionality
What we’re looking for:
- Experience building AI systems beyond basic LLM usage
- Exposure to agents, orchestration frameworks, or complex LLM pipelines
- Strong software engineering skills
- Comfortable working in production environments, not just research or prototypes
Nice to have:
- Experience with multi-agent systems, long-term memory, or tool use
- Background in distributed systems or real-time environments
- Familiarity with frameworks like LangChain, LlamaIndex, or similar
Machine Learning Engineer employer: Thyme
Contact Detail:
Thyme Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨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 personal connections can lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving agentic systems or multi-agent frameworks. We love seeing real-world applications of your work, so make it shine!
✨Tip Number 3
Prepare for technical interviews by brushing up on your software engineering skills. We recommend practicing coding challenges and system design questions that focus on production environments and complex workflows.
✨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’re always on the lookout for passionate candidates who want to push the boundaries of AI.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI and machine learning shine through. We want to see that you’re not just ticking boxes but genuinely excited about building agent-driven systems and pushing the boundaries of what's possible.
Tailor Your Experience: Make sure to highlight your experience with AI systems beyond basic LLM usage. If you've worked on multi-agent systems or have exposure to orchestration frameworks, shout about it! We love seeing how your background aligns with what we’re doing.
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured applications that get straight to the heart of your skills and experiences. Avoid jargon unless it’s relevant, and make sure we can easily see how you fit into our team.
Apply Through Our Website: Don’t forget to apply 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 to join our community at StudySmarter!
How to prepare for a job interview at Thyme
✨Know Your Stuff
Make sure you brush up on your knowledge of agent-driven systems and orchestration frameworks. Be ready to discuss your experience with complex LLM pipelines and how you've integrated models into real systems. This will show that you’re not just familiar with the theory but have practical experience too.
✨Showcase Your Projects
Prepare to talk about specific projects where you've designed and built AI systems. Highlight any challenges you faced and how you overcame them, especially in production environments. This gives the interviewer a clear picture of your problem-solving skills and hands-on experience.
✨Collaborate Like a Pro
Since collaboration is key in this role, think of examples where you worked closely with product or platform teams. Discuss how you contributed to shipping end-to-end AI functionality and how you navigated any team dynamics. This will demonstrate your ability to work well in a team setting.
✨Stay Current with Trends
Familiarise yourself with the latest trends in multi-agent systems and tools like LangChain or LlamaIndex. Being able to discuss these frameworks and their applications will show your enthusiasm for the field and your commitment to staying updated, which is crucial for a Machine Learning Engineer.