Senior MLOps Engineer

Drivers of change, it’s your time to pave new ways. Intellias, a leading software provider in the automotive industry, invites you to develop the future of driving. Join the team and create products used by 2 billion people in the world.

We are searching for an ML Engineer that can support our Data Science team on an interim basis developing, implementing and maintaining AI/ML solutions. The work will have a clear focus on defining technical requirements and implementing those solutions at scale, as well as implementing data pipelines for feature engineering. A close collaboration with Data Scientists and Data Engineers ensures that the Business Requirements are understood, and the solution is connected to the data flow.

We are a team of 4 Data Scientists working on solutions for the business. Among others, we developed algorithms for predicting the probability of default of our customers; churn; fraud; cross-and-upselling potential. We are working agile (2week sprints) and enjoy discussions over the topics at hand. Each Data Scientist is currently responsible for different projects and products. The ML Engineer will be required to support multiple projects/products and work with the entire team.

Requirements:

Must Have:

• Infrastructure as Code (IaC): Experience in provisioning and managing Azure resources (Azure ML, Key Vault, Storage Accounts) using Terraform or Bicep.
• Automation & CI/CD: Expert knowledge in building and maintaining Azure DevOps pipelines specifically for ML(automated testing, deployment, and model versioning).
• Security & Compliance: Proficiency in implementing security standards for sensitive data, including RBAC, encryption at rest/transit, and securing workspaces within Azure VNETs.
• Monitoring & Observability: Experience setting up monitoring for model drift, system performance, and cost tracking (e.g., Azure Monitor, Application Insights).
• Containerization: Strong knowledge of Docker and Azure Kubernetes Service (AKS) or Azure Container Instances (ACI) for model serving.
• Collaborative Mindset: Ability to define "Production Readiness" criteria and guide ML Engineers on best practices for code modularity and scalability.

Nice-to-Have:

• Certification in Azure Solutions Architecture or Azure AI Engineer.
• Experience with MLflow for experiment tracking and model registry.

Responsibilities:

• Build and maintain the underlying infrastructure for our Sales Transformation AI models.
• Primary goal is to ensure that the models operate in a secure, scalable, and automated environment.
• You will be responsible for the "industrialization" of the platform—ensuring that security standards are met, pipelines are fail-safe, and the infrastructure supports high-availability requirements for real-time sales triggers.

Why this position:

At Intellias, where technology takes center stage, people always come before processes. We're dedicated to cultivating a tech-savvy environment that empowers individuals to unlock their true potential and achieve extraordinary results. Our customized benefits not only prioritize your well-being but also charge your professional growth, making this opportunity an ideal match for tech enthusiasts like you.