Senior AI/ML Engineer - Production Systems & MLOps on GCP

Veritaz AB

Denmark

Remote

DKK 900,000 - 1,200,000

Full time

5 days ago

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Job summary

Veritaz AB is seeking a Senior AI Engineer / Machine Learning Engineer to design, build, and operate production-grade AI/ML solutions. The role focuses on turning prototypes into scalable cloud-native applications on Google Cloud Platform, using Terraform for IaC and Docker/Kubernetes for deployment.

You will collaborate with data scientists, engineers and product stakeholders to deliver secure and governed AI platforms.

Qualifications

Master's degree or higher in Computer Science, Software Engineering, Mathematics, Statistics, Physics or related field.
Strong software engineering background.
Excellent Python programming skills.
Proven experience designing, developing, deploying and operating production-grade AI solutions.
Strong understanding of software architecture and distributed systems.
Experience with cloud-native application development.
Experience with MLOps and/or LLMOps.
Knowledge of CI/CD, version control, automation, monitoring and observability.
Hands-on experience with Google Cloud Platform (GCP).
Experience with Infrastructure as Code, preferably Terraform.
Hands-on experience with Docker and Kubernetes.
Ability to turn AI/ML prototypes into production-ready applications.
Strong problem-solving and engineering judgment.
Ability to independently drive initiatives from concept through production.
Strong collaboration and communication skills.
Pragmatic, hands-on and delivery-focused mindset.

Responsibilities

Design and develop production-grade AI and ML solutions.
Build and operate AI-powered applications and platforms.
Translate business and analytical requirements into scalable production solutions.
Work with Python for AI/ML and software engineering.
Implement MLOps and LLMOps practices.
Build CI/CD pipelines, automation, monitoring and observability.
Develop and manage solutions on Google Cloud Platform (GCP).
Manage cloud infrastructure using IaC and Terraform.
Work with Docker and Kubernetes.
Transform Data Science prototypes and models into production-ready solutions.
Develop scalable and maintainable cloud-native applications.
Collaborate with Data Scientists, Data Engineers, Product Owners and business stakeholders.
Contribute to AI tooling, platforms and infrastructure supporting AI products at scale.
Support secure, reliable and governed AI solutions in production.