Remote Senior MLOps Engineer

Description:

• The Senior MLOps Engineer will build and maintain MLOps pipelines for seamless development, deployment, and monitoring of ML models.
• This role involves automating model training, evaluation, and deployment processes.
• The engineer will monitor model performance in real-time and implement solutions for drift detection.
• Responsibilities include designing and managing cloud infrastructure to support ML model deployment and scalability.
• The position requires optimizing resource usage and cost-efficiency on cloud platforms such as AWS, GCP, and Azure.
• The engineer will also automate CI/CD pipelines for both backend and frontend systems.

Requirements:

• Candidates must have strong experience with MLOps tools and platforms, including MLflow, Kubeflow, and SageMaker.
• Expertise in cloud platforms such as AWS, GCP, and Azure, along with infrastructure-as-code tools like Terraform and CloudFormation, is required.
• Proficiency in scripting and automation using languages such as Python, Bash, and Ansible is necessary.
• Knowledge of container orchestration and deployment tools, including Kubernetes and Docker, is essential.
• Familiarity with monitoring and logging tools, such as Prometheus and Grafana, is expected.
• Experience with version control and CI/CD practices is required.
• A strong understanding of the ML model lifecycle and deployment challenges is essential for this role.

Benefits:

• The position offers the opportunity to work with top-notch organizations and talents globally.
• Employees will have the chance to contribute to innovative MLOps solutions and practices.
• The role provides a dynamic work environment that encourages professional growth and development.
• Competitive compensation and benefits package will be offered to the successful candidate.