ML OPS Engineer

Rise provides fully programmatic media solutions for publishers that seamlessly integrate with their content and product user experience. With advanced data-powered solutions perfectly adapted to accommodate advertising needs, publishers are enabled to maximize their revenues by getting back control.

We are looking for our first ML OPS Engineer to join our Data Infra team in order to build and maintain the foundational ML services, tooling, and automation for Rise’s Tapjoy Ad Serving Platform. You will work in a dynamic, collaborative company culture with cutting-edge technologies. You will be responsible for our ML pipelines and infrastructure, automating and improving current flows, Production dev environments, and more.

Responsibilities:

• Collaborate with data science teams in order to understand how to optimize their processes
• Develop automated pipelines for deploying machine learning models to production environments..
• Set up and manage infrastructure for hosting machine learning models, including cloud-based platforms (e.g., AWS, GCP, etc.).
• Collaborate with data engineers to establish robust data pipelines for model training and inference.
• Develop Continuous Integration and Continuous Deployment (CI/CD) pipelines for model deployment and updates.
• Optimize model inference and prediction speed for high throughput and low latency.

Requirements:

• At least 2 years of experience as a ML Ops Engineer - MUST!
• Experience with AWS Sagemaker / google Vertex AI or similar - MUST
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
• Knowledge of orchestration tools like Kubernetes and Docker.
• Coding proficiency in Python programming languages
• Previous experience in deploying and managing machine learning models in production.
• Desire to learn and grow as you work on a highly performant ad serving platform.
• Production experience with managing data pipelines and streaming tools such as Kafka, MSK or Kinesis

Advantages:

• Hands-on experience with IAC tools like: Terraform, Cloudformation, Pulumi
• Experience with ML tools like Kubeflow, MLflow and Seldon core etc.