MLOps Engineer

Job summary

The MLOps Engineer role involves building, deploying, and maintaining production-ready machine learning solutions with a focus on MLOps practices such as CI/CD, model serving, and monitoring. Responsibilities include developing CI/CD pipelines, managing scalable deployments with containerization and Kubernetes, and collaborating with engineering and data science teams to enhance AI infrastructure and operational scalability.

Qualifications

• Experience in delivering machine learning or MLOps systems into production environments
• Proficiency in Python for building services, APIs, scripts and CI/CD automation
• Working knowledge of modern MLOps stacks including experiment tracking and artifact management
• Hands-on experience with orchestration tools (e.g., Kubeflow, Apache Airflow, Metaflow or Prefect)
• Demonstrated skills with Docker, Kubernetes and distributed deployments
• Practical knowledge of Infrastructure-as-Code (Terraform) and a major cloud provider (AWS, Azure or GCP)
• Familiarity with ML model serving, scaling and monitoring frameworks in production
• Strong communications skills to convey technical decisions and engage with clients effectively

Responsibilities

• Build and maintain platform components for ML model training, deployment, serving and monitoring
• Develop and optimize CI/CD pipelines for machine learning workflows
• Implement and support model lifecycle management, including registries and observability tooling
• Design and manage scalable, secure deployments using containerization and Kubernetes
• Enable secure, reusable and automated workflows to enhance ML developer productivity
• Extend platform capabilities to support LLMOps, RAG and agentic AI workloads
• Collaborate with engineering teams to improve reliability, automation and operational maturity
• Apply governance and compliance standards across AI operations
• Participate in presales and client-facing sessions to translate requirements into scalable solutions
• Advocate cloud best practices for reliability, scalability and cost optimization

Skills

Certifications

Degrees

Relocation