At a Glance
- Tasks: Build and deploy machine learning models while collaborating with data scientists and engineers.
- Company: Few&Far, a dynamic company at the forefront of machine learning innovation.
- Benefits: Competitive salary, hands-on experience, and opportunities for professional growth.
- Other info: Join a vibrant team in London and shape the future of data-driven decision making.
- Why this job: Make a real impact in a fast-paced environment with cutting-edge technology.
- Qualifications: Experience in machine learning and strong collaboration skills required.
The predicted salary is between 63000 - 77000 £ per year.
Few&Far is seeking a Machine Learning Engineer for an in-person role in London.
You will work with data scientists, engineers, and product teams to build models, shape data pipelines, and power decision making across a large, fast-moving network.
Youll design data architecture, deploy production ML, and develop ETL pipelines from diverse sources while collaborating with stakeholders to ensure data is used effectively.
The role emphasizes hands-on development and practical impact.
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London On-Site ML Engineer — Equity & Production ML employer: Few&Far
Join a pioneering AI and robotics startup in London as a Founding Engineer, where you'll have the unique opportunity to shape cutting-edge technology from the ground up. With a strong emphasis on collaboration and innovation, this role offers genuine ownership and the chance to work alongside an exceptional founding team, backed by world-class investors. The vibrant work culture fosters personal growth and encourages tackling complex engineering challenges, making it an ideal environment for those looking to make a meaningful impact in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land London On-Site ML Engineer — Equity & Production ML
✨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 Few&Far!
✨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 London On-Site ML Engineer — Equity & Production ML at Few&Far.
✨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 Few&Far.
✨Apply Directly through Our Website
When you find a suitable opening like London On-Site ML Engineer — Equity & Production ML at Few&Far, 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 London On-Site ML Engineer — Equity & Production ML
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 Few&Far, 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 Few&Far. 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 Few&Far
✨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 Few&Far!
✨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.
