A.P. Moller - Maersk

We Offer

Joining Maersk will embark you on a transformational journey. As a Machine Learning Engineer within the Network Operational Intelligence team, you will design and run AI-driven capabilities for our Global Network Automation stack. You will build the "brains" behind our network moving Maersk from reactive monitoring to proactive, self-healing autonomous networks. You will engage with stakeholders globally to evolve our operational tooling into a world-class AI-driven ecosystem.

The Brief

The Technology Function is fundamental to Maersk s strategy to become the global integrator of container logistics. We are recruiting world-class talent to ensure technology services are modernized. This role is central to the Network Architecture & Engineering function, responsible for the delivery of product roadmaps and technical vision across Network Assurance and Operational Intelligence.

Why this job matters

Reporting to the Senior Engineering Manager, you will serve as a technical lead for ML-driven network solutions. You will be responsible for the design and delivery of intelligent systems that handle everything from alarm correlation to zero-touch remediation . You will bridge the gap between massive network telemetry datasets and actionable business value.

Scope

The team is focusing on building intelligent, autonomous systems across Core, Edge, and Cloud (warehouses, terminals, vessels, data centers). You will focus on building network monitoring solutions through Generative AI and Real-time Stream Processing integrated into network elements spread across various geographies.

Key areas include:

Intelligent Streaming & Correlation: Building pipelines for real-time structured datasets (NetFlow, SNMP, gNMI telemetry) using Apache Flink or Spark Streaming .
Network ML Ops: Implementing Amazon SageMaker for model lifecycle management. Specifically focusing on Alarm/Telemetry Correlation using Association Rule Mining, FP-Growth, or Graph Neural Networks (GNNs) for topology-aware issue detection.
Scalable Observability: Leveraging the Grafana Stack (Loki, Mimir, Tempo) for high-cardinality telemetry visualization and intelligent alerting.
Data Lakehouse Engineering: Utilizing Databricks and Delta Lake for time-series network data analysis and handling seasonal traffic drifts.

Specific Job Requirements

We are looking for a Senior Engineer with 4+ years of experience in software/data engineering with a passion for building AI-driven infrastructure.

You will:

Collaborate with Network SMEs to identify AI opportunities in alarm fatigue reduction , root cause analysis (RCA), and operational summarization.
Lead the implementation of large-scale telemetry processing using Pyspark and Databricks .
Develop ML models that handle anomaly detection in network traffic and automate the correlation of disparate log sources.
Deploy and monitor models in production using SageMaker , ensuring they are robust enough for global-scale network operations.
Continuously evaluate emerging LLM and ML frameworks for use in the network automation space.

Required Skills and Qualifications:

Data & Streaming: Strong proficiency in Pyspark , Apache Flink , and Databricks . Experience managing large-scale Spark clusters for long-running ML jobs.
ML & AI Stack: Hands-on experience with Amazon SageMaker for model training and deployment. Knowledge of correlation algorithms (Association Rules, Clustering) and Time-Series Analysis.
Observability: Advanced knowledge of the Grafana Stack (Grafana, Prometheus, Alloy). Familiarity with OpenTelemetry (OTel) is a major plus.
Languages: Expert-level Python (for ML/Data Science) and familiarity with Java/Scala for streaming pipelines.
Network Domain: Understanding of network protocols (SNMP, Syslog, gNMI/gRPC) and telemetry formats.
Cloud & CI/CD: Expertise in AWS/Azure infrastructure and building GitHub Actions or GitLab CI pipelines for ML model deployments.
Database: Experience with Time-Series databases and NoSQL (ClickHouse, Elasticsearch, or Neo4j).

The Candidate

Demonstrates excellent communication skills with the ability to explain complex ML concepts to network engineers and business leaders.
A clear understanding of business imperatives and how AI-driven efficiency aligns with the Maersk "Global Integrator" strategy.
A fit with the culture and values of Maersk: constant care, uprightness, and humbleness.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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