About this role
Who we Are
At Grant Thornton Greece, we’re not just part of a global network of 76,000 professionals across 156 countries. We’re independent thinkers who prioritize quality, inclusion, and integrity to create a better, more personal experience for our clients and our team. Our mission? To deliver expertise in a way that goes beyond — Personal, Proactive, and Agile.
We don’t predict the future here—we shape it. 🚀
Milestones WE are Proud of
🏆 Great Place to Work certified for four years running!
🌟Best Workplaces Hellas for 2025!
👩💼 Best Workplaces for Women for three consecutive years!
⭐Best Workplace in Professional Services & Consulting for 2025!
🌈 Proud members of the Diversity Charter Greece and certified with the SHARE Equality Label
🏠 Flexible way of Working (Hybrid)
🧠Coaching & Counseling from Senior Professionals
The role in detail
As a Senior Machine Learning Engineer, you will play a pivotal role in designing, building, and scaling end-to-end machine learning solutions that drive measurable business value. You will work hands-on with predictive and machine learning techniques—such as logistic regression, random forests, gradient boosting models, and neural networks—leveraging modern ML frameworks and big data platforms to solve complex, real-world problems. A core responsibility of the role is to lead deep analytical exploration in ambiguous problem spaces, taking ownership from data understanding and model development through to deployment in cloud environments. You will collaborate cross-functionally with data, engineering, and business stakeholders, clearly communicating complex technical concepts and insights to non-technical audiences through impactful visualizations and storytelling. This role is ideal for a technically strong, forward-thinking professional who thrives in fast-moving environments and wants to shape scalable, production-ready AI solutions with tangible impact.
The key responsibilities of this role will include:
Designing, developing, and deploying scalable machine learning models using predictive techniques such as logistic regression, random forests, gradient boosting, and neural networks to address complex business problems.
Working hands-on with large-scale datasets and big data platforms, applying robust data processing and feature engineering techniques to support high-quality model performance.
Leading end-to-end machine learning initiatives, from problem definition and data exploration through model training, evaluation, and production deployment in cloud environments.
Collaborating closely with cross-functional teams, including engineering, data, and business stakeholders, to translate business requirements into effective machine learning solutions.
Communicating complex technical concepts, model behavior, and insights clearly to non-technical audiences through data visualization, storytelling, and structured presentations.
Utilizing modern machine learning frameworks and libraries to build maintainable, efficient, and well-documented solutions aligned with best engineering practices.
Driving continuous improvement and innovation by exploring new methodologies, tools, and technologies while proactively tackling ambiguous and high-impact analytical challenges.
To be successful in this role, you will need:
5+ years of hands-on experience in machine learning engineering, algorithm development, and working with large-scale data platforms in production environments.
Strong understanding of machine learning and predictive modeling techniques, including logistic regression, random forests, gradient boosting methods, and neural networks.
Proven experience building, deploying, and maintaining production-ready ML systems, including model training, evaluation, versioning, and monitoring.
Hands-on expertise with ML frameworks and libraries such as scikit-learn, TensorFlow, and PyTorch.
Solid engineering mindset, with experience in MLOps practices, CI/CD pipelines for ML, and containerization technologies (e.g., Docker, Kubernetes).
Experience working in cloud environments (AWS, Azure, or Google Cloud) for scalable data processing and model deployment.
Exposure to big data technologies and distributed data processing frameworks (e.g., Spark, Hadoop) is highly desirable.
Strong problem-solving skills and the ability to operate effectively in complex, ambiguous problem spaces with undefined outcomes.
Ability to communicate complex technical concepts clearly to non-technical stakeholders and translate business needs into effective ML solutions.
Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; Master’s degree or PhD is considered a strong plus.
Experience with data visualization or reporting tools (e.g., Power BI, Tableau) is a plus, but not a core requirement.
What’s in it for You?
At Grant Thornton Greece, we believe that great work deserves great rewards! Here’s what you can look forward to:
🌈 Diverse and inclusive workplace
🏋️♂️ Friendly, Dynamic Working environment
💰 Competitive Salary & Bonus
🩺 Insurance Program for all GT members
👩🏫 Fully funded Training & Professional Qualifications
🏖 Extra Days-off: August Freedays, Volunteering Days, Early leave days
🏃🏽♂️ Corporate Sports Teams (e.g., Running, Basketball, Volleyball)
🎁 Exclusive Discounts: Special offers and discounts for employees
🚗 Company Car (depending on job level)
Ready to Go Beyond?
If you're imagining a career that’s anything but ordinary, then Grant Thornton Greece is the place for you! We don’t just do business as usual—we go beyond. Ready to take that leap?
Simply upload your up-to-date CV, hit "apply", and we’ll handle the rest! ✨
We are Grant Thornton. We go beyond business as usual, so you can too.
#WelcomeToMore #GoBeyondWithUs