Mlops Engineer

Required Technical Skills

5+ years of experience working with an object-oriented programming language (Python, Golang, Java, C/C++ etc.)

Experience with MLOps frameworks like MLflow, Kubeflow, etc.

Proficiency in programming (Python, R, SQL)

Ability to design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)

Strong understanding of DevOps principles and practices, CI/CD, etc. and tools (Git, GitHub, jFrog Artifactory, Azure DevOps, etc.)

Experience with containerization technologies like Docker and Kubernetes

Strong communication and collaboration skills

Ability to help work with a team to create User Stories and Tasks out of higher-level requirements.

Nice to Have:

Ability to create model inference systems with advanced deployment methods that integrate with other MLOps components like MLFlow.

Knowledge of inference systems like Seldon, Kubeflow, etc.

Knowledge of deploying applications and systems in Langfuse or Kubernetes using Helm and Helmfile.

Knowledge of infrastructure orchestration using ClodFormation or Terraform

Exposure to observability tools (such as Evidently AI)