Machine Learning Engineer

Quick Facts

• Role: Machine Learning Engineer (ML Platform)

Description

The ML Platform team builds secure, scalable machine learning platform capabilities that enable Ads teams to improve and scale ML features, models, and applications at high performance and privacy. You will design and develop back-end systems, ML infrastructure used by multiple teams, and automation tooling that supports continuous experimentation and reliable deployment. The work focuses on end-to-end production ML systems, developer experience, and selecting the right technologies for ad-network challenges.

Responsibilities

• Write mission-critical production code for machine learning systems

• Build ML infrastructure, frameworks, or services used by multiple teams

• Develop SDKs, APIs, and automation UIs for development teams

• Build automation and CI/CD

Requirements

• MS in Computer Science or related field with industrial internship experience in machine learning; or BS in Computer Science or related field with 2+ years of industrial engineering experience including 1+ years of machine learning experience

• Passion for improving developer experience for AI/ML practitioners

• Understanding of the ML lifecycle: training, evaluation, deployment, and serving/inference; experience building and deploying models

• Working knowledge of deep learning architectures and training frameworks such as PyTorch or TensorFlow

• Strong problem solving, debugging, and performance tuning skills

• Results-oriented with effective written and verbal communication across technical and non-technical teams

Benefits

• Culture emphasizing reliability, simplicity, and scalability

• Opportunity to apply leading-edge ML technologies to deliver privacy-preserving advertising experiences

• Collaboration with a team of world-class machine learning engineers