Bombe
Junior Machine Learning Engineer
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Junior Machine Learning Engineer
At Bombe we are building the best customer insights platform in the world.
Bombe is on a mission to help businesses understand exactly what drives their customers, and machine learning is at the heart of how we do it. We're looking for a bright, ambitious Junior Machine Learning Engineer with a real passion for ML to join our technical team.
If you want to build models that make it into production and drive real decisions for real clients, and to learn fast alongside an experienced team in a growing AI scale up, this is a brilliant place to start your career.
About Bombe
Bombe combines machine learning with proprietary polling data to predict what customers will buy, where, and why, with an accuracy of up to 90%. We connect directly into clients' sales systems to turn that insight into revenue: spotting underperforming markets, sharpening targeting, and helping brands, venues, non-profits and public sector organisations make smarter, faster decisions.
Co-founded in 2024 by CEO Mike Joslin, who spent his career applying data strategy to major political campaigns before turning his focus to business, Bombe has already been featured in the BBC, Politico and The Guardian. We're a close knit, ambitious team based at Level39 in One Canada Square, Canary Wharf, and we're growing fast.
The Role
This is an entry level, learning focused role in our technical team, working closely with our Data Leadership. You'll get hands-on with the models behind the Bombe platform, from preparing data and building features to training, testing and improving the models our clients rely on. You'll have structured support to grow your skills, regular exposure to the CEO and leadership team, and real ownership of the work you deliver.
What You'll Be Doing
- Helping build, train and evaluate machine learning models that predict customer behaviour and revenue
- Cleaning, exploring and preparing large datasets, including our proprietary polling data and client sales data
- Engineering features and running experiments to improve model accuracy and performance
- Writing clean, well tested Python code and contributing to our shared codebase
- Supporting the deployment and monitoring of models in production, so they stay reliable and accurate over time
- Building data pipelines that connect client systems to the Bombe platform
- Documenting your models, experiments and findings clearly so the whole team can build on them
- Keeping up with new developments in ML and AI, and bringing fresh ideas to the team
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What We're Looking For
- A genuine passion for machine learning, whether through study, personal projects, Kaggle competitions or open-source work
- A degree (or equivalent experience) in computer science, maths, statistics, physics, engineering or another quantitative subject
- Some experience writing Python (or equivalent language such as R). E.g. through study or personal projects.
- An understanding of core supervised learning (regression and classification) and how common models such as linear regression, decision trees and KNN work.
- An understanding of how to evaluate a model fairly, e.g. train/test splits, cross-validation, common metrics, and spotting overfitting.
- A curious, analytical mind and a love of solving hard problems
- Ambitious and driven - you want to learn fast and take on more responsibility as you grow
- Clear communication skills, including explaining technical ideas to non technical stakeholders
- Enthusiasm towards continuously learning and developing new skills.
Bonus Points If You Have
- Strong data science skills using libraries such as Pandas, NumPy, scikit-learn, etc
- Exposure to gradient boosting (LightGBM, XGBoost, CatBoost), time-series forecasting or model calibration.
- Experience with Relational Database Management Systems including writing SQL (PostgresSQL or BigQuery)
- Experience cleaning and sanitising large or messy real world datasets
- Exposure to cloud platforms (AWS, GCP or Azure), Git, or MLOps tools
- An interest in socio-economic insights, polling, consumer behaviour, marketing or predictive analytics
- Experience of application / web software development
- Experience setting up and/or configuring CI/CD pipelines
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What You'll Get
- £30,000 per year
- 25 days' annual leave
- NEST workplace pension scheme
- Hybrid working, with a minimum of 3 days a week from our Canary Wharf office
- Mentoring from experienced engineers and a structured path to progress as the business grows
- Real ML work from day one, on a product that's already changing how organisations make decisions
- A central London base with excellent transport links via the Elizabeth line and Jubilee line
Right to work
To be eligible for this role you must have continued right to work within the UK. Unfortunately we cannot accept candidates who require VISA sponsorship
Our Hiring Ethos:
We believe the best teams are built from different experiences, backgrounds and ways of thinking. We are committed to creating an inclusive workplace where everyone is treated with respect, has the opportunity to succeed and feels able to be themselves. We welcome applications from people of all backgrounds and particularly encourage applications from groups that are underrepresented in our industry. We recruit based on talent, potential and what you can bring to the team. If you need any reasonable adjustments at any stage of the recruitment process, please let us know. You do not need to tick every box in the job description to apply. If you think you could make a real contribution, we would love to hear from you.
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