AI role · Open offer
Senior ML Engineer — logistics & supply chain
Maersk
This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.
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At a glance
How you'll work, where, and key listing dates.
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- Esplanaden 50, 1098 Copenhagen, Denmark · Hybrid
- Compensation
- DKK 650k–900k/year + bonus
- Experience level
- Senior
- Team
- Trade & logistics AI
- Benefits & perks
About this role
What the team is looking for and how this position fits.
Maersk is hiring a Senior Senior ML Engineer — logistics & supply chain on the Trade & logistics AI team (Hybrid · Copenhagen, Denmark). This is a hands-on role in NLP & language AI—not a generic “AI enthusiast” post.
You will own language understanding, generation, and quality metrics end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.
**Maersk** is a global **shipping and logistics** leader — container transport, ports, and supply-chain data — digitizing operations from **Copenhagen**.
Senior ML Engineer (hybrid Copenhagen): **demand forecasting**, **route optimization**, and **document AI** on trade paperwork.
About Maersk
- Danish multinational HQ at Esplanaden, Copenhagen.
- Data from vessels, ports, and customs feeds enterprise AI.
- Sustainability and efficiency goals drive model priorities.
What you will do
- Forecast container demand and capacity across trade lanes.
- Build OCR/NLP on bills of lading and customs documents.
- Deploy models with monitoring for supply-chain disruptions.
Stack & environment
- Python, PyTorch, Spark, Azure.
- Hybrid Copenhagen.
What we look for
- Time-series, logistics, or document AI experience.
- Eligible to work in Denmark.
Skills we're hiring for
What each capability means for this role—not a keyword checklist.
- Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
- PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
- SQL
Tools & stack
Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).
- AzureTool
Regular use of Azure in the NLP & language AI stack—configuration, debugging, and team conventions.
- KubernetesTool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
You're a strong fit if…
Tailored to this listing—use it as a self-check before you apply.
- ✓You can show evidence in your application: Forecasting, routing, or document intelligence for global logistics.
- ✓Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, Spark, and Azure.
- ✓You have owned language understanding, generation, and quality metrics in production: debugging live issues, running postmortems, and iterating from real user or business signals.
- ✓You are comfortable with the hybrid rhythm (Hybrid · Copenhagen, Denmark)—onsite collaboration when it matters, deep work when remote.
- ✓You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
Apply
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What the employer asked for
Forecasting, routing, or document intelligence for global logistics.
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