Global IT Digital

CEVA Logistics provides global supply chain solutions to connect people, products, and providers all around the world. Present in 170+ countries and with more than 110,000 employees spread over 1,500 sites, we are proud to be a Top 5 global 3PL.
We believe that our employees are the key to our success. We want to engage and empower our diverse, global team to co-create value with our customers through our solutions in contract logistics and air, ocean, ground, and finished vehicle transport. That is why CEVA Logistics offers a dynamic and exceptional work environment that fosters personal growth, innovation, and continuous improvement.
DARE TO GROW Join CEVA Logistics, and you will be part of a team that values imagination and continued learning and is committed to excellence in everything we do. Join us in our mission to shape the future of global logistics. As we continue growing at a fast pace, will you “Dare to Grow” with us?
Assist in designing and developing machine learning models to address business challenges, under the guidance of senior data scientists.
Support the deployment of AI use cases, helping to transition proof-of-concept models into scalable, production-ready solutions.
Gain hands-on experience with MLOps tools (e.g., Docker, Jenkins, MLflow) to automate model deployment and monitoring workflows.
Work with cloud platforms (AWS, Azure, or Google Cloud) to manage and process AI/ML workloads.
Use Python and SQL to analyze and manipulate datasets, with mentorship to enhance technical proficiency.
Participate in model monitoring and retraining activities to ensure AI solutions deliver consistent performance.
Collaborate with cross-functional teams to understand business requirements and contribute to AI-driven solutions.
Prepare reports and visualizations to communicate findings and project progress to team members.
**Qualifications and Skills**:
**Educational Background**:
Current enrollment in the final year of a Bachelor’s or Master’s degree program in Computer Science, Data Science, Engineering, Mathematics, or a related field.
Completion of coursework in machine learning, statistics, or data analysis is a plus.
**Technical Skills**:
Foundational knowledge of Python and familiarity with libraries such as scikit-learn, TensorFlow, or PyTorch.
Basic understanding of machine learning algorithms and statistical methods.
Familiarity with SQL for data querying and management.
Exposure to cloud platforms (AWS, Google Cloud or Azure) or containerization tools (e.g., Docker) is a plus.
Interest in MLOps practices and tools like MLflow, Kubeflow, or Jenkins.
Basic experience with data visualization tools (e.g., Streamlit, or Qlik Sense) is a plus.
**Soft Skills**:
Enthusiastic and eager to learn, with a proactive approach to tackling challenges.
Strong collaboration skills and the ability to work effectively in a team environment.
Clear communication skills, with the ability to articulate ideas and seek guidance when needed.
Organized and detail-oriented, with the ability to manage multiple tasks and meet project deadlines.
Adaptable to a fast-paced, dynamic work environment.
WHAT DO WE HAVE TO OFFER YOU?
With a genuine culture of diversity and recognition of work, we want our employees to grow, evolve, and become an integral part of our journey. There's no doubt that you will be rewarded in line with your commitment, so if you want to work for one of the best logistics solution providers worldwide, get in touch with us, and let’s define your next challenge together.
**Additional Information**:
This 6-month internship provides exposure to CEVA’s state-of-the-art Data Platform and modern cloud-based tools, offering a practical learning experience in a global logistics leader. Interns will receive mentorship from experienced professionals, opportunities to work on impactful projects, and the chance to build a foundation for a career in data science and MLOps. The role is ideal for final-year students seeking to bridge academic knowledge with industry experience.
If you are a motivated final-year engineering or master’s student with a passion for data science and MLOps, and are eager to contribute to innovative solutions, we encourage you to apply.