Our Company:
QiH is a fast-growing, innovative, and progressive scale-up business headquartered in London with a collective of brilliant brains in Skopje. We are at the start of an exciting journey as we build out our internal engineering capability, spearheading our tech transformation, building best in class products and tackling exciting and complex challenges along the way!
Data is at the core of what we do at QiH, but our people are at the heart of our success! At QiH, we have created an energetic and target-driven culture and continuously invest in each individual.
The Role
We are seeking an experienced Senior Machine Learning Engineer to join our dynamic team.
You’ll be at the forefront of designing, developing, and deploying ML models that power personalised advertising, customer journey analytics, audience segmentation, and real-time bidding strategies.
Working closely with BI, data engineers, and product teams, you'll build scalable solutions that drive measurable business outcomes for some of the world's most recognised brands.
Our infrastructure is powered by Google Cloud Platform (GCP), and we pride ourselves on applying cutting-edge techniques to real-world marketing and advertising challenges.
Key Responsibilities:
Design, build, and deploy scalable machine learning models for ad targeting, user segmentation, conversion prediction, and content personalization.
Develop production-grade ML pipelines leveraging GCP services like Vertex AI, BigQuery, Dataflow, and Pub/Sub.
Collaborate cross-functionally with Data Science, Data Engineering, and Product teams to translate business objectives into ML solutions.
Research and implement state-of-the-art techniques in deep learning, reinforcement learning, and large-scale optimization relevant to Ad Tech and Mar Tech.
Monitor, troubleshoot, and continuously improve model performance in production environments.
Mentor junior engineers and promote best practices in model development, code quality, and cloud infrastructure usage.
Contribute to the evolution of our ML Ops processes including continuous training, automated evaluation, and scalable deployment frameworks.
Maintain high standards for documentation, security, and model explainability in compliance with industry regulations (GDPR, CCPA, etc.).
Participate in architecture design sessions and provide input into strategic decisions regarding AI/ML tooling and GCP adoption.
About You:
Experience: 5+ years of experience in machine learning engineering, preferably in Ad Tech, Mar Tech, or related high-scale environments.
Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Deep understanding of supervised, unsupervised, and reinforcement learning methods.
Experience with GCP services such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, and Dataproc.
Solid knowledge of distributed systems, data streaming (e.g., Apache Beam, Kafka), and large-scale data processing.
ML Ops: Hands-on experience with continuous integration/deployment (CI/CD) for ML, model versioning, and monitoring.
Business Acumen: Ability to understand marketing and advertising concepts like customer lifetime value (CLV), attribution modeling, real-time bidding (RTB), and audience targeting.
Strong understanding of data pipeline orchestration tools (e.g., Apache Airflow, Kubernetes).
You thrive when working as part of a team
Comfortable in a fast-paced environment
Have excellent written and verbal English skills
Last but not least, you’ll have no ego!
What You’ll Get:
Competitive Basic Salary
Quarterly Bonuses
Hybrid working
Private Health Care (Bupa)
Market Leading Training Programme
Recognition & Reward Scheme
Annual Company Conference (previous destinations Bologna, Dubrovnik, Belgrade and Thessaloniki)
Regular Happy Hour / Team Lunches
Free Coffee, Drinks & Snacks
What’s the next step?
Our hiring process ensures we're recruiting the right people for the role. We ensure that people are as suitable for us as we are for them.
If you like the sound of what we're all about at QiH and want to join a team where you can make an impact, please apply or contact us at [email protected].
