At a Glance
- Tasks: Drive innovative research in machine learning to solve real-world scientific problems.
- Company: Exciting London-based AI lab focused on impactful scientific advancements.
- Benefits: Competitive salary, equity options, and a comprehensive benefits package.
- Other info: Flexible hybrid work model and a supportive, inclusive environment.
- Why this job: Join a passionate team and make a tangible difference in AI-driven discoveries.
- Qualifications: PhD in relevant field with strong ML research and coding skills.
The predicted salary is between 60000 - 80000 £ per year.
About the company
We are a London-based, early-stage AI lab building AI systems that help scientists learn from real-world experimentation and accelerate the path to commercially valuable materials. Our mission is to combine machine learning, automation and deep domain expertise to solve hard scientific problems with real-world impact. We are a small, ambitious team bringing together strong ML, engineering and materials science capability. We value pace, rigour, curiosity and low ego, and we want people who are energised by working on focused problems where their contribution is visible from day one. We offer a flexible hybrid working model, regular collaboration in London, and an inclusive environment where people from all backgrounds are welcomed and supported.
What the job entails
As a Research Scientist, Machine Learning, you will own research problems at the intersection of modelling, reasoning and experiment automation. Your work will help power an AI-driven discovery engine by improving how the system learns from sparse, noisy and high-dimensional scientific data. You will design and prototype novel ML approaches, develop active learning and optimisation methods that decide which experiments should run next, and work closely with materials scientists and chemists to translate scientific constraints into rigorous mathematical models and loss functions. You will take ideas from theory through to proof-of-concept, establish strong baselines, and partner with engineers to scale successful approaches into production. The role is hands-on and requires both research depth and production-quality coding.
Key requirements / What we look for
- PhD in machine learning, computer science, physics or a related field;
- Strong track record in novel ML research and evaluation;
- Strong Python skills; PyTorch or equivalent, plus production-quality code;
- Experience with Linux, Git and HPC/cloud platforms;
Compensation & Benefits
Competitive base salary. Generous equity, with performance- and scope-based additional awards. Benefits package.
Machine Learning Researcher employer: Generative
As a Machine Learning Researcher at our London-based AI lab, you'll be part of a dynamic and ambitious team dedicated to solving significant scientific challenges through innovative AI solutions. We foster a collaborative and inclusive work culture that values curiosity and low ego, offering flexible hybrid working arrangements and opportunities for professional growth in a supportive environment. Join us to make a tangible impact from day one, as you contribute to cutting-edge research that accelerates the discovery of commercially valuable materials.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Researcher
✨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 Generative!
✨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 Machine Learning Researcher at Generative.
✨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 Generative.
✨Apply Directly through Our Website
When you find a suitable opening like Machine Learning Researcher at Generative, 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 Machine Learning Researcher
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 Generative, 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 Generative. 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 Generative
✨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 Generative!
✨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.
