As part of AI Hub within Data Insights & AI Department (DIA), you will lead Hapag-Lloyd's AI transformation initiatives and AI adoption. Contributing to AI implementation across our organization, you will create new business value with AI technology for shipping and logistics applications for our 17,000+ colleagues.
In short: you will own the technical implementation and production of AI/ML solutions across the entire ML lifecycle: from model development and validation, through deployment and monitoring, to scaling and maintenance of production systems, while ensuring robust, reliable, and scalable AI solutions.
Responsibilities- Collaborate with AI Project Leads and business stakeholders to translate requirements into technical solutions
- Design, develop, and optimize machine learning models for shipping and logistics use cases
- Build robust ML pipelines for data preprocessing, feature engineering, model training, and evaluation
- Implement MLOps best practices including version control, automated testing, and continuous integration for ML workflows
- Lead production of AI/ML models, ensuring they meet enterprise-grade performance, reliability, and security standards
- Design and implement model deployment strategies including containerization, API development, and cloud-native solutions
- Build monitoring and alerting systems for model performance, data drift, and system health in production
- Establish automated retraining pipelines and model lifecycle management processes
- Mentor other team members on ML engineering best practices
5+ years of experience in machine learning engineering with proven track record of deploying ML models to production
Strong programming skills in Python, with expertise in ML (TensorFlow, PyTorch, scikit-learn)
Experience in MLOps tools and practices (MLflow, Docker, CI/CD pipelines)
Experience in data engineering tools and technologies (Databricks, Apache Spark, SQL databases), cloud platforms (AWS, Azure) and their ML services
Hands-on experience with model serving frameworks and API development (REST, microservices architecture)
Knowledge of monitoring and observability tools (Grafana, ELK stack)
Ability to translate complex technical concepts for non-technical stakeholders
Background in shipping, logistics, or similar operational industries preferred
Ability to work in fast-moving, global environments
Fluency in English; additional languages advantageous
Our global network spans 140 countries, 400 offices, and a growing portfolio of terminal and infrastructure investments. This scale enables us to deliver consistent, high‑quality service across continents and to support our customers in even the most complex supply chains.
When you join us, you become part of more than 18,000 colleagues working across borders, functions, and cultures, to not only to deliver quality for our customers, but to create innovation and opportunities across roles, regions, and perspectives.
We believe that every exploration is a chance to grow, and every port is a place to belong.
- Private medical care (Medicover)
- Gym card (Multisport)
- Attractive annual bonus up to 22,5% (depending on company performance results)
- Group life insurance and employee capital plan (PPK)
- Cafeteria benefit system (cinema tickets, vouchers etc.)
- Focus on healthy lifestyle (fruit days, bike competitions, football training)
- Charity and volunteer initiatives
- Modern and well-connected office (Alchemia complex in Gdańsk Oliwa)
- Relocation support (financial support, covering immigration process and polish-language lessons for non-Polish citizens)
- Internal learning management system
- Development budget (sharing the costs of certifications and conferences/ IT events)
- Flexible working hours and home office possibility (hybrid work model)
Skills Required
- 5+ years of experience in machine learning engineering with production deployments
- Strong programming skills in Python and expertise in ML libraries (TensorFlow, PyTorch, scikit-learn)
- Experience with MLOps tools and practices (MLflow, Docker, CI/CD pipelines)
- Experience with data engineering tools (Databricks, Apache Spark, SQL databases)
- Experience with cloud platforms and ML services (AWS, Azure)
- Hands-on experience with model serving and API development (REST, microservices architecture)
- Knowledge of monitoring and observability tools (Grafana, ELK stack)
- Ability to translate complex technical concepts for non-technical stakeholders
- Background in shipping, logistics, or similar operational industries
- Fluency in English (additional languages advantageous)
What We Do
With a fleet of 280 modern container ships and a total transport capacity of 2.1 million TEU, Hapag-Lloyd is one of the world’s leading liner shipping companies. In the Liner Shipping segment, the Company has around 13,700 employees and 400 offices in 140 countries. Hapag-Lloyd has a container capacity of 3.1 million TEU – including one of the largest and most modern fleets of reefer containers. A total of 114 liner services worldwide ensure fast and reliable connections between more than 600 ports on all the continents. In the Terminal & Infrastructure segment, Hapag-Lloyd has equity stakes in 20 terminals in Europe, Latin America, the United States, India, and North Africa. Around 2,900 employees are assigned to the Terminal & Infrastructure segment and provide complementary logistics services at selected locations in addition to the terminal activities.
.png)
