Machine Learning Engineering Lead
AplicarAre you looking for new challenges and personal growth within Coca-Cola Europacific Partners? Then we have a great opportunity for you!
Do you have a personality with the power to influence and connect?
Can you sustain the pace to keep on growing?
Will you make an impact with your desire to win?
Lead Machine Learning Engineer
About Coca-Cola Europacific Partners (CCEP)
CCEP is the world’s largest independent Coca-Cola bottler, operating across 13 countries and serving over 300 million consumers. Our portfolio includes iconic brands like Coca-Cola®, Fanta®, Powerade®, Glaceau Vitaminwater®, Monster®, and Capri-Sun®.
We’re on a journey to unlock the full potential of data and analytics across our business. With our first-ever Chief Data & Analytics Officer leading the way, we’re building a progressive data strategy that transforms insights into action—driving growth, efficiency, and sustainability.
The Role: Lead Machine Learning Engineer
As the Lead Machine Learning Engineer, you’ll be at the forefront of designing, developing, and deploying cutting-edge machine learning solutions. You’ll work closely with data scientists, engineers, and business stakeholders to operationalize models and build scalable ML pipelines that power our data-driven products and services.
Key Responsibilities
- Lead end-to-end development of ML models using Python, scikit-learn, Keras/TensorFlow.
- Architect and maintain scalable ML pipelines integrated with our data platforms.
- Implement advanced ML techniques (e.g., bagging, boosting, ensemble methods, neural networks).
- Monitor model performance and data drift; optimize reliability and accuracy.
- Define and track ML Ops metrics (accuracy, latency, drift, resource utilization).
- Collaborate with data scientists to productionize research models.
- Establish best practices for model versioning, reproducibility, and retraining.
- Mentor junior ML engineers and foster a culture of innovation.
- Stay ahead of industry trends and introduce new tools and techniques.
What We’re Looking For
Required Skills & Experience
- Proven leadership in ML engineering teams or projects.
- Expert in Python and ML libraries (scikit-learn, Keras, PyTorch, TensorFlow).
- Strong grasp of advanced ML techniques and ML Ops practices.
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Excellent problem-solving and stakeholder engagement skills.
- Bachelor’s or Master’s in Computer Science, Data Science, Engineering, or related field.
- Experience with big data tools (Spark, Hadoop).
- Familiarity with feature stores, model registries, and experiment tracking.
- Exposure to business domains like finance, healthcare, or retail analytics.
Why Join Us?
- Lead and shape the ML engineering function in a data-driven organisation.
- Work in a collaborative and innovative environment.
- Access continuous learning and professional development.
You Might Be the Right Fit If You…
- Are a hands-on Senior ML Engineer and team leader.
- Are passionate about high-quality delivery and coaching others.
- Value sustainable, flexible data platforms and their business impact.
- Combine software engineering discipline with data science rigor.
- Create an environment where your team thrives.
Ready to Make an Impact?
Apply now and be part of our data transformation journey.
Application
If this role is of interest to you please upload a recent copy of your CV and a member of the Talent Acquisition team will be in touch.
We believe that equal opportunities means inclusion, diversity and fair treatment for all.
We aim to make our recruitment process as comfortable and accessible as possible and would appreciate it if you would advise us of any particular requirements, adjustments or requests you may have to help us ensure that your experience is enjoyable.
Job Information:
Hiring Manager: Rajesh Mahajan
Recruiter: Tegan McColl
Grade: G2
Location: Pan EU : Belgium:Brussels/Bruxelles : Anderlecht(HQ) || Pan EU : Bulgaria:Sofia : Sofia City || Pan EU : France:Ile-de-France : Paris || Pan EU : Germany:Berlin : Head office national:10245 || Pan EU : Iceland:Reykjavik : Reykjavik || Pan EU : Norway:Akershus : Norway HQ- Lorenskog || Pan EU : Portugal:Lisboa e Vale Do Tejo : Lisboa || Pan EU : Spain:Cataluna : Barcelona || Pan EU : Spain:Madrid : Madrid || Pan EU : Sweden:Svealand : Stockholm - HQ || Pan EU : The Netherlands:Zuid Holland : Rotterdam(Hoofdkantoor) || Pan EU : United Kingdom:CCEP Site Locations : Uxbridge