At a Glance
- Tasks: Lead the development of ML systems and drive technical direction in a fintech scale-up.
- Company: Dynamic fintech scale-up where ML is at the core of the product.
- Benefits: Flexible hybrid working, competitive salary, and opportunities for growth.
- Other info: No need for an up-to-date resume; easy apply process to get started.
- Why this job: Shape the future of ML products that institutional investors rely on daily.
- Qualifications: Hands-on experience with multi-agent models and strong software engineering fundamentals.
The predicted salary is between 80000 - 100000 £ per year.
Want to join a fintech scale-up where ML isn't a side project, it's the core of the product?
They're growing out their ML team, and this is a chance to shape it from the front.
This is a hands‑on role focused on technical leadership, no people management required.
You’ll lead by example, drive development practices and technical direction, and own the end‑to‑end lifecycle of ML systems, from Gen AI features to the data pipelines behind them.
This is not a research role, you'll ship products to production that institutional investors rely on daily.
We’re looking for someone from a software development background with hands‑on agentic experience, bringing strong engineering fundamentals to their ML work.
What’s in it for you?
- Flexible, hybrid working from central London
- And much more
What you must have
- Hands‑on experience with multi‑agent models and workflows
What will make you stand out?
- A software engineering background with strong development processes and technical leadership
- Agentic build‑outs, using agents to call LLMs and embedding them into workflows
- Chat‑type applications and chat agents
- Python and AWS
No need for an up‑to‑date resume just yet, just click ‘easy apply’ and someone will reach out with more details. We can then help you build the best resume for the role later.
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StudySmarter Expert Advice🤫
We think this is how you could land Lead AI / ML 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 Tact!
✨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 Lead AI / ML Engineer at Tact.
✨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 Tact.
✨Apply Directly through Our Website
When you find a suitable opening like Lead AI / ML Engineer at Tact, 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 Lead AI / ML 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 Tact, 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 Tact. 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 Tact
✨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 Tact!
✨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.
