Tech Stack

Description

You will help bridge the gap between research and production by building and optimizing scalable ML infrastructure, including data pipelines, dashboards, and monitoring systems. You'll assist in operating ML job frameworks, maintaining internal API servers, and creating tools to simplify ML workflows.

Requirements

• Bachelor's degree in Computer Science, Engineering, or related field (Master's preferred)
• 2+ years of experience in ML or engineering
• Proficiency in Python, Java, or Go with solid understanding of data structures and algorithms
• Familiarity with LLM-powered tools like GitHub Copilot or ChatGPT
• Understanding of core ML and deep learning concepts

Responsibilities

• Assist in operating robust ML job execution frameworks for training, inference, and post-processing
• Build and maintain internal API servers and developer tools to orchestrate ML jobs on Kubernetes
• Implement data infrastructure and monitoring tools like Prometheus and Grafana
• Create internal tools and services to simplify ML experimentation and production workflows
• Collaborate with senior ML engineers and scientists to turn research outputs into product features