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- Tasks: Lead technical development and innovate in ad fraud detection using machine learning.
- Company: Fast-growing UK-based SaaS scale-up focused on digital advertising.
- Benefits: Competitive salary, hybrid work model, and impactful projects.
- Why this job: Join a dynamic team and shape the future of ad technology.
- Qualifications: 5+ years Python experience, big data expertise, and a proactive mindset.
- Other info: Opportunity for rapid career growth in a high-autonomy environment.
The predicted salary is between 64000 - 88000 £ per year.
This UK-based SaaS scale-up is on a mission to protect advertisers’ digital spend by detecting and blocking invalid or low-value clicks. Using machine learning and real-time behavioural analytics, they help agencies and large advertisers improve ROI and reduce waste—all while being cookieless and privacy-compliant. With £15M in Series A funding and integrations with major ad platforms, this is your chance to lead a high-impact engineering team in a fast-growing, data-driven environment.
As a Staff Engineer, you’ll be a technical leader in the Platform Team, focusing on hands-on development, architecture, and mentorship. You’ll work with real ML datasets, Rubix data, and large-scale ad traffic analytics, building features for the Data Science team and launching new ML models. This role is not about people management—it’s about owning technical design, writing high-quality code, and driving innovation.
Specifically, you can expect to be involved in the following:
- Technical tasks: Improving real-time traffic tracking, deploying new ML models, and optimizing big data pipelines.
- Collaboration: Working closely with Product, Data Science, and engineering teams to solve complex problems.
The successful Staff Engineer will have the following skills and experience:
- 5+ years of Python engineering experience, with a focus on big data, ML, or adtech.
- Deep hands-on expertise in Python and an understanding of JavaScript/TypeScript/React (even if you won’t write it daily).
- Experience with large-scale datasets, AWS (Redshift is a bonus), or other cloud platforms (GCP/Azure).
- Familiarity with ad platforms (Meta Marketing API, Google Ads API) is a huge plus.
- A computer science/STEM degree is preferred, but strong self-taught candidates will be considered.
- Thrives in fast-paced, high-autonomy environments—stable tenure and a proactive mindset are key.
The successful Staff Engineer will receive the following benefits:
- £80,000–£110,000 salary (depending on location and experience)
- Hybrid working policy: 2 days/week in-office (London/Manchester)
- High-impact work: Shape the future of ad fraud detection and optimization.
- Fast growth: Join a scale-up with a clear trajectory and work with cutting-edge ML and big data.
- Twice-weekly production deployments: See your work make an immediate difference.
Please register your interest by sending your resume/CV to Joana Alves via the Apply link on this page.
Staff Engineer in London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those related to Python, ML, or big data. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding system design. Practice common algorithms and data structures to impress during those hands-on assessments.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Staff Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your Python engineering experience, especially in big data and ML, to show us you're the right fit for the Staff Engineer role.
Showcase Your Projects: Include any relevant projects or experiences that demonstrate your hands-on expertise with large-scale datasets and cloud platforms. We love seeing real examples of your work, so don’t hold back!
Keep It Clear and Concise: When writing your application, be clear and to the point. Use bullet points where possible to make it easy for us to read through your qualifications and achievements quickly.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Harnham
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills, especially in big data and machine learning. Be ready to discuss specific projects you've worked on, particularly those involving large datasets or cloud platforms like AWS. This will show that you’re not just familiar with the tech but have hands-on experience.
✨Understand the Company’s Mission
Dive deep into the company’s mission of protecting advertisers’ digital spend. Familiarise yourself with their approach to ad fraud detection and how they leverage machine learning. This knowledge will help you align your answers with their goals and demonstrate your genuine interest in the role.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and coding abilities. Practice coding challenges related to Python and big data. You might also be asked about optimising data pipelines or deploying ML models, so be ready to showcase your thought process and solutions.
✨Showcase Your Collaborative Spirit
Since the role involves working closely with Product and Data Science teams, be prepared to discuss how you’ve successfully collaborated in past projects. Highlight your ability to communicate complex technical concepts to non-technical stakeholders, as this will be crucial in a cross-functional environment.
