A.P. Moller - Maersk is an integrated container logistics company that is responsible for moving 20% of global trade every year. With a dedicated team of over 100,000 employees across 130 countries, we go all the way to connect and simplify global trade and help our customers grow and thrive. Maersk’s vision is to be the global integrator of logistics, connecting and simplifying customers’ supply chains.
As an AI/ML Engineer in our Data & AI Governance team, you will help build and maintain AI/ML-driven capabilities that improve how Maersk detects, manages, and resolves data quality issues while supporting responsible AI observability and governance. This is a hands-on engineering role focused on developing and operating solutions for data reliability, metadata intelligence, and AI lifecycle monitoring.
You will work alongside senior engineers, architects, and product teams to build scalable capabilities that improve trust, quality, and transparency across enterprise data and AI platforms.
The role sits at the intersection of data engineering, AI/ML, and governance, making it ideal for someone who enjoys solving practical engineering challenges while contributing to the reliability and responsible use of data and AI.What I'll be doing – your accountabilities?
- Build and maintain AI/ML-driven components to detect data anomalies, schema drift, and degradation across data pipelines
- Develop validation rules, profiling capabilities, and scoring mechanisms for enterprise data quality monitoring
- Apply AI/ML techniques such as classification, anomaly detection, and NLP to support metadata enrichment and quality analysis
- Support implementation of responsible AI capabilities including model monitoring, explainability, and lifecycle logging
- Partner with platform engineers to integrate solutions into orchestration and MLOps platforms
- Work with data owners and stewards to operationalize data quality ownership through MIDAS
- Maersk’s enterprise AI platform for metadata inventory, data accountability, and governance
- Support DataOps processes, quality standards, and operational excellence initiatives
- Participate in troubleshooting, root cause analysis, and continuous improvement activities
- Contribute to engineering documentation, testing, and deployment practices
- Collaborate with cross-functional teams to deliver scalable and reliable AI and data quality solutions
- Foundational Skills : Strong Python programming skills
- Understanding of machine learning concepts including anomaly detection, classification, clustering, and predictive analytics
- Knowledge of data engineering fundamentals including data pipelines, data quality, data observability, and metadata management
- Experience working with structured and semi-structured data at scale
- Understanding of cloud platforms and modern data architectures
- Knowledge of software engineering best practices including testing, CI/CD, version control, and code reviews Familiarity with monitoring, observability, and operational health metrics
- Strong analytical, problem-solving, and troubleshooting skills Ability to work effectively in Agile and cross-functional teams
- Specialized Skills :Experience applying AI/ML techniques to data quality, anomaly detection, drift detection, profiling, or metadata enrichment
- Familiarity with Generative AI, LLMs, prompt engineering, embeddings, vector databases, and RAG architectures
- Understanding of AI observability, model monitoring, and explainability concepts
- Familiarity with metadata platforms, lineage, data catalogues, or governance tooling
- Exposure to DataOps, MLOps, and enterprise AI lifecycle management
- Eagerness to learn and contribute to AI governance frameworks (e.g., EU AI Act, ISO 42001, NIST AI RMF) and translate those into engineering patterns
- Qualifications &
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field4-5 years of experience in Software Engineering, Data Engineering, AI Engineering, Machine Learning, or related disciplines
- Experience building, deploying, or supporting AI, ML, data, or software solutions in production or enterprise environments
- Familiarity with machine learning frameworks and AI development toolchains
- Exposure to cloud-native data and AI services
- Experience working within Agile product or engineering teams
- Strong communication and stakeholder collaboration skills
- Ability to learn quickly, adapt to new technologies, and contribute in a fast-paced environment
- Passion for building reliable, scalable, and trustworthy AI solutions
- Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking.
- Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law.
- We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.
- We are happy to support your need for any adjustments during the application and hiring process.
- If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.
