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: yyou will build, deploy, and operate cloud-native AI/ML services on AWS with a strong focus on Python engineering, Cloud DevOps, Linux-based runtime environments, and production operations. This role is about productionalization and platform/service engineering – not about ML research, model experimentation, or leading model design.
Responsibilities- Collaborate closely with Data Scientists and Data Engineers to productionalize processing and inferencing code, models and data products
- Collaborate with AI Project Leads and business stakeholders to translate requirements into production-ready cloud solutions
- Develop and maintain Python-based services, pipelines, and automation for AI/ML use cases
- Design, build, and operate AWS/Databricks infrastructure for AI/ML workloads
- Implement Cloud DevOps practices: CI/CD pipelines, infrastructure-as-code, automated deployments, and environment management
- Build and operate containerized workloads and API-based integrations
- Implement monitoring, alerting, and operational dashboards for service health, cost, and ML-related signals (e.g., data drift)
- Support model lifecycle operations (versioning, deployment, rollback, retraining automation) in collaboration with Data Scientists
- 5+ years of experience in Python engineering for production systems
- Strong AWS hands-on experience with services like VPC, EC2, S3, RDS, Lambda, CloudWatch ECS/EKS
- Proven Cloud DevOps experience: CI/CD pipelines, Git-based workflows, infrastructure-as-code (Terraform), release management
- Solid Linux skills (shell, networking basics, troubleshooting, logs/metrics, process and resource management)
- Experience with containerization and runtime operations
- Experience with Python ML libraries or eagerness to learn on those (PyTorch, scikit-learn)
- Experience with data engineering tools and technologies like Databricks, Apache Spark, SQL databases is a plusMLOps experience like MLflow, model serving, monitoring concepts is a plus
- Ability to translate complex technical concepts for non-technical stakeholders
- Ability to work in interdisciplinary team of various AI competencies
- Fluency in English
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.
