Applied Scientist, Ads Decision Science (AI)

TL;DR

Applied Scientist, Ads Decision Science (AI): Building autonomous AI systems to deliver personalized advertising solutions and optimal recommendations across multiple communication channels. Focus on asking research questions about advertiser behavior, developing state-of-the-art recommender models, and deploying these models directly on ad delivery channels.

Location: Onsite in New York, USA

Salary: $172,400–$223,400 USD annually

Company

hirify.global is revolutionizing marketing technology by creating interactive conversational agents, content generation capabilities, and recommender systems to personalize communication strategies for advertisers.

What you will do

• Build autonomous AI systems to proactively identify advertiser pain points and deliver optimal recommendations.
• Ask research questions about advertiser behavior and develop state-of-the-art recommender models.
• Deploy models directly on ad delivery channels to benefit advertisers and the retail business.
• Measure the impact of your work using scientific tools.
• Participate in the Amazon ML community and mentor Applied Scientists and software development engineers.
• Make an enormous impact on the design, architecture, and implementation of new generation ads products.

Requirements

• 3+ years of experience building models for business applications.
• PhD, or Master's degree and 4+ years of experience in CS, CE, ML, or a related field.
• Experience programming in Java, C++, Python, or related languages.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.
• Must be able to work onsite in New York, USA.
• English: B2 proficiency is required.

Nice to have

• Experience using Unix/Linux.
• Experience in professional software development.

Culture & Benefits

• Comprehensive benefits package including health insurance (medical, dental, vision), 401(k) matching, paid time off, and parental leave.
• Inclusive culture that empowers Amazonians to deliver the best results for customers.
• Opportunity to participate in the Amazon ML community.
• Support for disability accommodations or adjustments during the application and hiring process.