We are looking for our first MLops engineer to join our Research Team in order to build and maintain the foundational ML services, tooling, and automation for CPU and GPU-based algorithms. 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, and more.

Responsibilities:

• Work alongside data science teams in order to understand how to optimize their processes.
• Set up and manage infrastructure for hosting machine learning models, including cloud-based platforms (e.g., AWS) and container orchestration (e.g., Kubernetes).
• Collaborate with data engineers to establish robust data pipelines for model training and inference.
• Optimize model inference post-process algorithm for high throughput and low latency.
  
  

Requirements:

• At least 2 years of experience as an MLops Engineer – MUST!
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
• Knowledge of orchestration tools like Kubernetes and Docker.
• Coding proficiency in Python programming languages.
• Desire to learn and grow as you work on a highly performant ad-serving platform.