Offer summary

Qualifications:

Strong experience with MLOps tools and platforms such as MLflow and Kubeflow., Expertise in cloud platforms like AWS, GCP, and Azure., Proficiency in scripting and automation using Python and Bash., Knowledge of container orchestration tools like Kubernetes and Docker..

Key responsabilities:

Build and maintain MLOps pipelines for ML model development and deployment.

Automate model training, evaluation, and deployment processes.

Monitor model performance and implement solutions for drift detection.

Design and manage cloud infrastructure to support ML model scalability.

Job description

Octopus by RTG is on a mission of connecting top notch ogranizations around the globe with top notch talents. We are currently looking for a Senior MLOps Engineer

Responsibilities:

Build and maintain MLOps pipelines for seamless development, deployment, and monitoring of ML models.
Automate model training, evaluation, and deployment processes.
Monitor model performance in real-time and implement solutions for drift detection.
Design and manage cloud infrastructure to support ML model deployment and scalability.
Optimize resource usage and cost-efficiency on cloud platforms (e.g., AWS, GCP, Azure).
Automate CI/CD pipelines for both backend and frontend systems.

Requirements

Strong experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, SageMaker).
Expertise in cloud platforms (AWS, GCP, Azure) and infrastructure-as-code tools (e.g., Terraform, CloudFormation).
Proficiency in scripting and automation (e.g., Python, Bash, Ansible).
Knowledge of container orchestration and deployment (e.g., Kubernetes, Docker).
Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana).
Experience with version control and CI/CD practices.
Strong understanding of ML model lifecycle and deployment challenges.

Required profile