Senior AI Engineer — Remote, Scalable ML & MLOps

Jysk

Denmark

On-site

DKK 900,000 - 1,300,000

Full time

10 days ago

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Benefits offered by this job

Staff discounts
Internal training

Job summary

JYSK is seeking a Senior AI Engineer to drive the end-to-end AI lifecycle—from model development and training to deployment and operation at scale. You will bridge software engineering with advanced ML to create scalable, business-driven AI solutions that improve processes and customer experiences.

Responsibilities include building end-to-end AI apps and MLOps pipelines, designing Retrieval-Augmented Generation workflows, and collaborating with data, platform, and software engineers on

Qualifications

  • 5+ years of industry experience in software engineering and AI solutions at scale.
  • Experience deploying and operating AI models in production.
  • Hands-on with RAG systems, LLMs, and retrieval-augmented workflows.
  • Strong Python and ML tooling experience.

Responsibilities

  • Develop and scale end-to-end AI applications and MLOps pipelines.
  • Design, develop, and deploy AI agent systems and tooling.
  • Build RAG pipelines and semantic search integrations.
  • Experiment with models across NLP, CV, and generative approaches.
  • Collaborate with data, platform, and software engineers.
  • Manage AI workloads on cloud infrastructure to optimize performance.

Skills

Python
ML/AI systems
GCP/AWS/Azure
NLP/CV/Deep Learning
MLOps

Education

Bachelor's degree in CS/Software Eng/Math/Phys
PhD in related field (advantage)

Tools

Google Cloud Platform (GCP)
Azure / AWS
RAG pipelines

Job description

JYSK is seeking a Senior AI Engineer to drive the end-to-end AI lifecycle—from model development and training to deployment and operation at scale. You will bridge software engineering with advanced ML to create scalable, business-driven AI solutions that improve processes and customer experiences.

Responsibilities include building end-to-end AI apps and MLOps pipelines, designing Retrieval-Augmented Generation workflows, and collaborating with data, platform, and software engineers on

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