At a Glance
- Tasks: Build cutting-edge AI prediction software and shape the future of human behaviour modelling.
- Company: Join a pioneering stealth startup focused on innovative AI solutions.
- Benefits: Competitive salary, equity options, and a hybrid work environment.
- Other info: Fast-paced startup culture with opportunities for growth and collaboration.
- Why this job: Directly influence product direction and make impactful decisions in AI technology.
- Qualifications: 5+ years in AI/ML systems, strong data engineering skills, and Python proficiency.
The predicted salary is between 80000 - 100000 £ per year.
We're helping a leading, early-stage stealth startup building AI-based prediction software. Their core mission is to accurately predict human behaviour at scale. You will be responsible for building production-grade LLM and agentic workflows that drive critical business decision-making for their users. This means turning customer, market, and operational data into reliable reasoning contexts for their models, and designing robust evaluation, tracing, replay, and quality-control systems for nondeterministic AI outputs. You'll work on counterfactual analysis, forecasting, customer behaviour modelling, and decision support, constantly improving reliability through structured outputs, retrieval, constraints, calibration, tests, and model comparisons.
Expect to build internal tools that make these AI workflows repeatable across various customer segments and use cases, and to directly help define how the team measures the usefulness, accuracy, and trustworthiness of the AI's predictions. You'll work directly with the founders on product direction, customer problems, and technical architecture, shaping the future of their product.
Compensation: Competitive salary + equity
Commitment: Full-time
Location: London / Hybrid
Start date: As soon as possible
Key requirements:
- 5+ years of experience building and deploying production-grade AI/ML systems, with a focus on LLMs or agentic workflows
- Strong background in data engineering and MLOps, particularly in turning unstructured data into reliable model inputs
- Experience with designing and implementing evaluation and quality-control systems for AI outputs
- Proficiency in Python and relevant AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face)
- Ability to work independently and collaboratively in a fast-paced, early-stage startup environment
Founding AI Engineer in London employer: Ethos
Join a pioneering early-stage startup in London, where innovation meets collaboration. As a Founding AI Engineer, you'll be at the forefront of developing cutting-edge AI solutions that drive impactful business decisions, all while enjoying a dynamic work culture that fosters creativity and growth. With competitive compensation and equity options, this role offers not just a job, but a chance to shape the future of AI technology alongside visionary founders.
StudySmarter Expert Advice🤫
We think this is how you could land Founding AI Engineer in London
✨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 Ethos!
✨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 Founding AI Engineer at Ethos.
✨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 Ethos.
✨Apply Directly through Our Website
When you find a suitable opening like Founding AI Engineer at Ethos, 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 Founding AI Engineer in London
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 Ethos, 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 Ethos. 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 Ethos
✨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 Ethos!
✨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.
