Wave Group
Machine Learning Engineer

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Machine Learning Engineer
Remote, Europe | (UK, Germany, Spain)
About the role
A growth-stage cybersecurity company is hiring a Machine Learning Engineer to embed AI capabilities into its Web Application Firewall and bot mitigation product. You'll work directly with the Head of AI, using live web traffic data to build models that detect malicious traffic, bots and anomalies.
There's no data engineering function in place yet, so a large part of the role is your own data cleaning and feature engineering before you get to modelling. The brief prioritises a proactive, research-driven mindset over a fixed technical stack.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What you'll do
- Design, train and evaluate ML models to detect malicious traffic patterns and behavioural anomalies
- Build and maintain data pipelines from raw web traffic through to training-ready datasets
- Work primarily in Python, using standard ML tooling to build pre-production models
- Collaborate with product and engineering to hand models over for deployment
- Improve data quality and feature engineering as new threat patterns emerge
What's needed
- 3+ years as an ML Engineer, Data Scientist or similar, with production ML exposure
- Strong Python, comfortable with PyTorch, TensorFlow or scikit-learn
- Experience with large datasets and SQL-based systems
- Self-directed, comfortable defining your own approach to ambiguous problems
- Degree in Computer Science, Engineering, Mathematics or related field


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Your very own career expert that helps elevate your application to the next level.
Useful but not essential
- Fraud, bot detection or traffic analysis experience
- Exposure to LLMs or generative AI frameworks
- Some C++
- Experience with cloud data tooling (BigQuery, Spark, Airflow)
Location
Must be based in, and hold the legal right to work in, the UK, Germany, Spain or Estonia.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
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