At a Glance
- Tasks: Design and build cutting-edge AI agents and scalable machine learning systems.
- Company: Join a high-performing AI research group at the forefront of innovation.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional growth.
- Other info: Collaborate with top-tier researchers in a dynamic, high-output environment.
- Why this job: Make a real impact in the world of AI with groundbreaking projects.
- Qualifications: 2-4 years in machine learning, strong Python skills, and a research background.
The predicted salary is between 50000 - 70000 £ per year.
Contract length: 6 months with potential to extend
Location: Hybrid 3 days per week in King's Cross
We are hiring a Machine Learning Research Engineer to join a high-performing AI research group working at the forefront of large language models and autonomous AI agents. This is not a traditional engineering role. You will operate at the intersection of research and applied systems, building next-generation AI capabilities that push beyond current industry benchmarks.
What you will do:
- Design and build LLM-driven agents for research and automation
- Develop scalable machine learning systems using Python and PyTorch
- Run complex experiments across large datasets and models
- Collaborate with researchers and engineers to deliver measurable scientific impact
- Contribute to cutting-edge work influencing real-world AI systems
What we are looking for:
- 2–4 years’ experience in machine learning, AI, or related fields
- Strong Python and PyTorch capability
- Exposure to LLMs, generative AI, or agent-based systems
- Strong academic or research grounding (Maths, Physics, ML)
- High-output mindset with the ability to execute quickly
- High-performance, research-led team
- Direct exposure to world-class AI work
Next steps to apply:
Apply now with word document CV or email your CV to rory@principlehr.com for immediate review.
Machine Learning Research Engineer (LLM & AI Agents) employer: Principle
Join a leading global technology organisation that values its employees and fosters a collaborative work culture. With a focus on professional growth, you will have the opportunity to enhance your skills in contingent workforce operations while enjoying a hybrid work model in Reading, Berkshire. The company offers competitive salaries and a supportive environment that encourages innovation and teamwork, making it an excellent place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Research Engineer (LLM & AI Agents)
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We think you need these skills to ace Machine Learning Research Engineer (LLM & AI Agents)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Principle, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Principle. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Principle
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Principle!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
