ML/MLOps engineer to $5000

Requirements:

2+ years of experience in MLOps/ML.

Strong knowledge of Python and SQL.

Experience with ML libraries (TensorFlow, PyTorch, NumPy etc.).

Experience in machine learning model deployments and pipelines.

Experience with MLOps frameworks/tools (e.g. Sagemaker pipelines/ Azure ML Studio/ VertexAI/ Kubeflow/ MLFlow).

Understanding of data integration, and database management.

Quick learning abilities.

English upper-intermediate оr higher.

Would be a plus:

Hands-on experience with Cloud Services(AWS, GCP, Azure).

Experience with Docker, Kubernetes, CI/CD, IaC, Prometheus, Grafana.

Responsibilities:

Develop, refine, and use ML engineering platforms and components, development workflow pipelines.

Deployment of open-source and other models to different instances.

Collaborate with ML architect  and data scientists to curate high-quality datasets and optimize data workflows.

Rapid model deployment implementation.

Developing process-related documentation.

Kubeflow and MLFlow upgrade.