AI Research Engineer

AI Research Engineer

Full-Time 63000 - 77000 £ / year (est.) On-site
I

At a Glance

  • Tasks: Join an AI research lab to innovate brain-inspired AI models and optimise their efficiency.
  • Company: Early-stage AI research lab focused on cutting-edge technology.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Exciting projects in a collaborative environment located in London.
  • Why this job: Make a real impact in the future of AI with your research and creativity.
  • Qualifications: Degree in a quantitative field and strong Python skills required.

The predicted salary is between 63000 - 77000 £ per year.

Our client, an early-stage AI research lab, is hiring Research Scientists and Research Engineers to work on brain-inspired, mathematically grounded approaches to making AI more efficient, with direct impact on how future models store and compute.

Focus areas (one or more):

  • Brain-inspired architectures (state-space, recurrent, associative-memory and long-context models)
  • Neural memory and dynamical systems modelling
  • Optimisation and neural-network training dynamics
  • Efficient AI (quantisation, sparsity, model compression, low-precision computation)
  • Spiking systems, neuromorphic computing and computational neuroscience
  • Hardware-aware machine learning (memory bandwidth, inference efficiency, energy modelling)
  • Experimental design and evaluation (baselines, ablations, robustness, computational cost)

Requirements:

  • Bachelor’s, Master’s or PhD in Maths, Neuroscience, Computer Science, Physics, Engineering or a closely related quantitative field
  • Strong foundations in several of: linear algebra, probability, optimisation, dynamical systems, numerical methods, information theory or statistical learning
  • Strong Python and PyTorch (or JAX) experience, with a solid understanding of transformers and LLM architectures
  • Rigorous experimental mindset, with the ability to move between mathematical reasoning, experimentation and implementation
  • Research publications, open-source contributions or substantial independent projects (industry experience not essential)

Location: London. Full-time, permanent.

If this role sounds interesting to you, please reach out to Charles Duran.

AI Research Engineer employer: Intellectual Capital Resources

Join a dynamic team where innovation meets collaboration, as we empower our Opto Mechanical Engineers to transform cutting-edge optical concepts into tangible products. Our supportive work culture fosters continuous learning and professional growth, with hands-on opportunities in a state-of-the-art laboratory environment. Located in a vibrant area, we offer competitive benefits and a chance to work alongside industry experts, making this an ideal place for those seeking meaningful and rewarding employment.

I

Contact Details:

Intellectual Capital Resources Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Research Engineer

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Intellectual Capital Resources!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Research Engineer at Intellectual Capital Resources.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Intellectual Capital Resources.

✨Apply Directly through Our Website

When you find a suitable opening like AI Research Engineer at Intellectual Capital Resources, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace AI Research Engineer

Brain-inspired architectures
Neural memory modelling
Dynamical systems modelling
Optimisation techniques
Neural-network training dynamics
Quantisation
Sparsity

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Intellectual Capital Resources, 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 Intellectual Capital Resources. 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 Intellectual Capital Resources

✨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!

✨Showcase Your Projects

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 Intellectual Capital Resources!

✨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.