Senior ML Engineer — Production AI & MLOps Lead

Cari; København; Hybrid; DKK 651,000 - 957,000; Full time

Job summary

Cari is seeking a Senior Machine Learning Engineer to turn models and AI prototypes into reliable production services. You will design, deploy and operate machine learning, generative AI and agent-based applications on Databricks, AWS and Azure, and set engineering practices that keep them performing.

Your work helps colleagues move from promising ideas to dependable tools they use every day, supporting progress for people living with serious chronic diseases.

Qualifications

• Degree in computer science, engineering, mathematics or related field, or equivalent practical experience.
• 5+ years in machine learning engineering, software engineering or applied AI with production ML systems.
• Strong hands-on Databricks expertise, including Python, PySpark, Spark SQL, Delta Lake, MLflow, production pipelines, model serving, workflow orchestration and Unity Catalog governance.
• Strong practical knowledge of AWS and Azure for deploying and operating ML or AI workloads, along with Git, CI/CD, containers and infrastructure as code, such as Terraform.
• Demonstrated implementation experience across MLOps, LLMOps, AgentOps and DataOps, from reproducible training, model registries and rollback to retrieval-augmented generation, safety testing, agent tracing, tool permissions, data contracts and lineage.
• Strong Python and SQL skills, solid machine learning fundamentals, experience with frameworks such as scikit-learn, PyTorch or TensorFlow, and practical experience building LLM applications with embeddings, retrieval, structured outputs and tool calling.
• Experience with observability, incident response and production support, an understanding of data privacy, security, responsible AI and model governance, and the communication skills to explain technical trade-offs and mentor colleagues.

Responsibilities

• Design, build, deploy and maintain ML models, LLM applications and AI agents, including batch and real-time inference services integrated into business applications.
• Build training, evaluation, deployment and monitoring workflows with Databricks and MLflow, and operate AI infrastructure on AWS and Azure that balances performance, reliability, security and cost.
• Establish MLOps, LLMOps, AgentOps and DataOps practices - covering versioning, automated testing, rollback, safety controls, human oversight and reliable, well-governed data.
• Monitor model quality, data drift, latency, availability and cost, investigate failures and define evaluation criteria that measure technical quality alongside business outcomes.
• Lead technical design discussions, review code, mentor engineers and document operational procedures to raise engineering standards across the team.

Skills

Databricks

Python

PySpark

Spark SQL

Delta Lake

MLflow

MLOps

LLMOps

DataOps

Git

CI/CD

Containers

Terraform

Kubernetes

AWS

Azure

Education

Bachelor's degree in CS or related field

Tools

Terraform

Docker

Kubernetes

Unity Catalog governance

Job description

Cari is seeking a Senior Machine Learning Engineer to turn models and AI prototypes into reliable production services. You will design, deploy and operate machine learning, generative AI and agent-based applications on Databricks, AWS and Azure, and set engineering practices that keep them performing.

Your work helps colleagues move from promising ideas to dependable tools they use every day, supporting progress for people living with serious chronic diseases.