A.P. Moller - Maersk
A.P. Moller – Maersk is the global leader in container shipping services. The business operates in 130 countries and employs c. 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers’ supply chains.
Job Role
AI/ML Platform Engineering focuses on building scalable engineering platforms, infrastructure, automation, and operational capabilities that enable AI and Machine Learning teams to develop, deploy, integrate, monitor, and operate AI/ML solutions efficiently and securely. AI/ML platforms provide standardized tools and services for model lifecycle management, MLOps, model serving, Generative AI, LLM applications, agentic AI, experimentation, deployment, observability, and governance. AI/ML Platform Engineering combines cloud infrastructure, software engineering, DevOps, MLOps, Kubernetes, automation, and AI technologies to create reliable and self-service platforms that accelerate enterprise AI adoption.
Data AI/ML (Artificial Intelligence and Machine Learning) Engineering involves the use of algorithms and statistical models to enable systems to analyze data, learn patterns, and make data-driven predictions or decisions without explicit human programming. AI/ML applications leverage vast amounts of data to identify insights, automate processes, and solve complex problems across a wide range of fields, including healthcare, finance, e-commerce, and more. AI/ML processes transform raw data into actionable intelligence, enabling automation, predictive analytics, and intelligent solutions. Data AI/ML combines advanced statistical modeling, computational power, and data engineering to build intelligent systems that can learn, adapt, and automate decisions.
• Independently design and implement scalable machine learning solutions and data systems, ensuring end to end workflows, large scale analytics and reliability
• Collaborate with stakeholders to translate business needs into data engineering solutions, evaluate user journeys and challenge business requirements to ensure seamless, value driven delivery and integration of solutions
• Implement and refine feature engineering, monitoring, ML pipelines, deploy models in production, and address challenges in data pipelines
• Apply innovative problem-solving techniques, leveraging advanced methodologies to find unique approaches to complex problems and improve outcomes
• Investigate and resolve complex challenges in data models and deployment to ensure reliable solutions that meet performance benchmarks
• Mentor team members through code reviews, pairing sessions, knowledge-sharing sessions, and contribute to Communities of Practice
• Communicate technology, infrastructure, and deployment decisions clearly to both technical and non-technical stakeholders while maintaining detailed documentation to ensure reproducibility, scalability, and understanding
• Ensure readiness for production releases, focusing on testing, monitoring, observability, and maintaining scalability and reusability of models for future projects
• Drive cross-team and cross-discipline initiatives to optimize workflows, remove redundant applications and processes, share best practices, and enhance collaboration between teams
• Demonstrate awareness of shared platform capabilities and actively identify opportunities to leverage them in designing efficient and scalable data engineering solutions
CORE SKILLS
AI & Machine Learning: Creating AI-powered solutions using Generative AI, Agentic AI and machine learning technologies to solve business problems and automate processes.
Proficiency Level: Proficient
Cloud Platform Engineering: Designing, deploying and operating secure, scalable and highly available cloud-native platforms on AWS.
Proficiency Level: Advanced
Programming: Writing production-grade applications, platform services and automation using languages such as Python, Java and SQL.
Proficiency Level: Advanced
MLOps & AI Operations: Automating the end-to-end lifecycle of AI models including deployment, monitoring, governance and optimization.
Proficiency Level: Advanced
DevSecOps & Automation: Using CI/CD pipelines, Infrastructure as Code and security controls to automate software development and platform operations.
Proficiency Level: Advanced
Distributed Systems: Designing scalable, resilient and fault-tolerant systems capable of supporting enterprise AI workloads.
Proficiency Level: Advanced
SPECIALIZED SKILLS
Generative AI & LLMs: Building applications using Large Language Models, Retrieval Augmented Generation (RAG), prompt engineering and AI agents.
Agentic AI Frameworks: Developing autonomous and multi-agent solutions using modern orchestration frameworks and enterprise AI patterns.
AI Platform Architecture: Designing reusable AI platform capabilities including model serving, inference orchestration and governance frameworks.
AWS Cloud Services: Leveraging services such as EKS, Lambda, Bedrock, API Gateway, S3, IAM, Step Functions and CloudWatch.
Containerization & Kubernetes: Deploying, managing and scaling containerized applications using Docker and Kubernetes.
Infrastructure as Code: Automating infrastructure provisioning and platform operations using Terraform and cloud-native tooling.
Observability & Reliability Engineering: Implementing monitoring, logging, tracing and performance optimization for platform services.
Security & Governance: Applying enterprise security practices including IAM, secrets management, compliance and responsible AI controls.
API & Integration Engineering: Building scalable APIs and integrating enterprise platforms, cloud services and AI solutions.
Technical Documentation: Creating architecture documents, operational runbooks and technical standards for enterprise platforms.
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.
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