AI role · Open offer

Senior ML Engineer — logistics & supply chain

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Maersk

Full-time
Senior
Trade & logistics AI
Hybrid
Esplanaden 50, 1098 Copenhagen, Denmark · Hybrid
DKK 650k–900k/year + bonus

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.).

KubernetesTool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
AzureTool
Regular use of Azure in the NLP & language AI stack—configuration, debugging, and team conventions.

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 Kubernetes.
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

Candidate accounts only: add your headline and bio on , and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Forecasting, routing, or document intelligence for global logistics.

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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