AI Research Scientist

Adamas Knight
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior NLP & AI Research Scientist

Senior NLP & AI Research Scientist - Hybrid

Remote Principal NLP Research Scientist: Lead AI Innovation

Senior Data Scientist - NLP AI Research

Remote AI Data Scientist — Contract, Flexible Renewal

Senior Data Scientist - NLP AI Research

About the job


Adamas Knight is recruiting for a groundbreaking AI Lab, backed by some of the biggest names in industry, working on building their own proprietary foundation model within the multi-modal domain - text and vision.


With one of the best compute in industry, they are looking for a senior RS that has been a core contributor to the pre- or post-training of an impactful large multimodal model to lead this whole initiative.


The Role


As aSenior Research Scientist, you will be at the forefront of developing large-scale, multimodal deep learning models from scratch. You will design and implement novel architectures capable of integrating diverse types of data, such as images, text, and structured information, to enable advanced, multi-faceted insights. Your work will involve exploring and experimenting with state-of-the-art techniques in deep learning, such as transformers, neural architecture search, and multimodal fusion, to create models that can handle complex, real-world tasks. You will push the boundaries of model performance, scalability, and generalization, laying the foundation for future breakthroughs in multimodal AI.


Benefits/Perks:


  • Attractive Compensation: Enjoy a competitive salary and the opportunity to invest in your future with equity in the company
  • Comprehensive Benefits: Access private healthcare, a gym allowance, and catered lunches to support your well-being
  • Work-Life Balance: Benefit from flexible working hours that fit your lifestyle



At Adamas Knight, we are committed to creating an inclusive culture. We do not discriminate based on race, religion, gender, national origin, sexual orientation, age, veteran status, disability, or any other legally protected status. Diversity is highly valued, and we encourage applicants from all backgrounds to apply.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.