Staff Machine Learning Engineer, Ads Attribution, 8+ Years of Experience

$222,000 - $333,000/Yr

Snap Inc. - Palo Alto, CA

Full-time - Senior

Palo Alto, CA

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

The Staff Machine Learning Engineer for Ads Attribution at Snap Inc. is responsible for building, optimizing, and deploying machine learning models that support identity resolution and ads attribution. This role involves collaborating with cross-functional teams to align machine learning strategies with company objectives, ensuring high code quality, and creating scalable products that drive value for users and advertisers.

Responsibilities

• Build, optimize, and deploy machine learning models to support identity resolution and ads attribution
• Create models which help drive value for users, advertisers, and the company
• Collaborate with cross-functional teams to align on machine learning strategies
• Stay up-to-date with the latest technology in machine learning and apply this knowledge
• Perform code reviews and ensure exceptional code quality
• Build robust, lasting, and scalable products
• Iterate quickly without compromising quality

Requirements

• Bachelor's degree in technical field such as computer science, mathematics, statistics or equivalent years of experience
• 8+ years machine learning experience in industry
• Experience building and applying machine learning models to ads attribution, identity, measurement, or privacy-preserving ML
• Strong understanding of machine learning approaches and algorithms
• Strong computer science fundamentals
• Skilled with unsupervised learning for unlabeled data
• Able to prioritize duties and work well independently
• Ability to work with both internal and external partners
• Skilled at solving open ambiguous problems
• Strong collaboration, leadership, and mentorship skills

Nice-to-haves

• Advanced degree in computer science or related field
• Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn
• Experience working on machine learning infrastructure and systems

Benefits

• Paid parental leave
• Comprehensive medical coverage
• Emotional and mental health support programs
• Compensation packages that include equity in the form of RSUs