Applied Scientist, Sponsored Products Off-Search Sourcing (AI)

TL;DR

Applied Scientist (AI): Designing and developing state-of-the-art Generative AI, deep learning, and reinforcement learning solutions for Amazon's advertising landscape, revolutionizing ad retrieval, auctions, and personalized shopping experiences. Focus on building novel generative models and fundamentally transforming ad allocation and customer engagement with ads at massive scale and impact.

Location: Must be based in the USA (Palo Alto, New York, or Seattle).

Salary: $142,800–$223,400 USD annually.

Company

hirify.global is re-imagining the advertising landscape through state-of-the-art generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond.

What you will do

• Contribute to the design and development of GenAI, deep learning, multi-objective optimization, and/or reinforcement learning empowered solutions.
• Transform ad retrieval, auctions, whole-page relevance, and bespoke shopping experiences.
• Collaborate cross-functionally with other scientists, engineers, and product managers to deliver scalable solutions.
• Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing innovative concepts and prototypes.
• Enhance scientific and technical rigor by implementing best-in-class algorithms and infrastructure.
• Mentor junior scientists and engineers, cultivating a high-performing and collaborative team.

Requirements

• PhD, or Master's degree and 4+ years of CS, CE, ML, or related field experience.
• 3+ years of experience building models for business application.
• Experience programming in Java, C++, Python or related language.
• Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.
• Experience developing and deploying models in real-world production environments.

Nice to have

• Proven expertise in Generative AI, foundation models, LLMs, and/or fine-tuning and customization for downstream tasks.
• Hands-on experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale.
• Deep understanding of multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF).
• Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce.
• Familiarity with auction theory, ad economics, and advertiser performance metrics.

Culture & Benefits

• Comprehensive benefits including health insurance (medical, dental, vision, prescription, life & AD&D insurance).
• Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.
• Opportunity to work on responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace.
• Work in an inclusive culture that empowers employees.