National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Machine Learning Engineer

QiH Group
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Our Company:

QiH is a fastgrowing innovative and progressive scaleup 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 targetdriven culture and continuously invest in each individual.

The Role

We are seeking an experienced Senior Machine Learning Engineer to join our dynamic team.

Youll be at the forefront of designing developing and deploying ML models that power personalised advertising customer journey analytics audience segmentation and realtime bidding strategies.

Working closely with BI data engineers and product teams youll build scalable solutions that drive measurable business outcomes for some of the worlds most recognised brands.

Our infrastructure is powered by Google Cloud Platform (GCP) and we pride ourselves on applying cuttingedge techniques to realworld 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 productiongrade ML pipelines leveraging GCP services like Vertex AI BigQuery Dataflow and Pub/Sub.

  • Collaborate crossfunctionally with Data Science Data Engineering and Product teams to translate business objectives into ML solutions.

  • Research and implement stateoftheart techniques in deep learning reinforcement learning and largescale 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 highscale environments.

  • Strong proficiency in Python and ML frameworks (TensorFlow PyTorch Scikitlearn).

  • 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 largescale data processing.

  • ML Ops: Handson 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 realtime 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 fastpaced environment

  • Have excellent written and verbal English skills

  • Last but not least youll have no ego!

What Youll 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

Whats the next step

Our hiring process ensures were 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 were all about at QiH and want to join a team where you can make an impact please apply or contact us at.


Required Experience:

Senior IC


Key Skills
Industrial Maintenance,Machining,Mechanical Knowledge,CNC,Precision Measuring Instruments,Schematics,Maintenance,Hydraulics,Plastics Injection Molding,Programmable Logic Controllers,Manufacturing,Troubleshooting
Employment Type :Full-Time
Experience:years
Vacancy:1

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.