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- Tasks: Lead technical design and develop innovative solutions in a fast-paced environment.
- Company: Join a dynamic UK-based SaaS scale-up focused on ad fraud detection.
- Benefits: Competitive salary, hybrid work model, and impactful projects.
- Why this job: Shape the future of advertising with cutting-edge machine learning technology.
- Qualifications: 5+ years Python experience, big data expertise, and a proactive mindset.
- Other info: Opportunity for rapid career growth in a collaborative team.
The predicted salary is between 68000 - 92000 £ 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 employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job 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 interviews by practising common technical questions and coding challenges. We recommend using platforms like LeetCode or HackerRank to sharpen your skills before the big day.
✨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 genuinely interested in joining us.
We think you need these skills to ace Staff Engineer
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 with 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 in Python and familiarity with ad 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 where you've used these technologies, as well as any experience with AWS or ad platforms. This will show that you're not just familiar with the tools, but that you can apply them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to talk about complex problems you've solved in previous roles. Think of examples where you improved processes or optimised systems, particularly in a fast-paced environment. This will demonstrate your ability to thrive under pressure and contribute to the team’s success.
✨Collaboration is Key
Since this role involves working closely with Product and Data Science teams, be ready to discuss how you've collaborated with cross-functional teams in the past. Highlight your communication skills and how you’ve contributed to team projects, as this will show you’re a team player who can drive innovation.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company’s approach to ad fraud detection and their use of machine learning. This shows your genuine interest in the role and helps you understand if the company culture aligns with your values. Plus, it gives you a chance to engage with your interviewers on a deeper level.
