Sr. Applied Scientist (AI)

TL;DR

Sr. Applied Scientist (AI): Develop generative AI, deep learning, and reinforcement learning solutions to transform ad retrieval, auctions, and personalized shopping experiences on Amazon’s off-search advertising surfaces. Focus on designing scalable AI models, collaborating cross-functionally, and mentoring junior scientists to innovate in advertising technology.

Location: Onsite in New York, NY or Seattle, WA, USA

Salary: $167,100–$248,700 USD annually

Company

hirify.global is a leading innovator in artificial intelligence technologies, focused on transforming advertising experiences through generative AI and machine learning at massive scale.

What you will do

• Design and develop GenAI, deep learning, multi-objective optimization, and reinforcement learning solutions for ad retrieval, auctions, and relevance.
• Collaborate with scientists, engineers, and product managers to deliver scalable, production-ready AI solutions.
• Stay current with industry trends in GenAI and LLMs, introducing innovative concepts and prototypes.
• Enhance scientific rigor by implementing best-in-class algorithms and infrastructure for rapid experimentation and scaling.
• Mentor and grow junior scientists and engineers, fostering a collaborative and high-performing team.

Requirements

• Must have a PhD or Master’s degree with 8+ years of applied research experience.
• 3+ years of experience building machine learning models for business applications.
• Proficiency in Java, C++, Python, or related programming languages.
• Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and optimization.
• Experience with vLLM, SGLang, TensorRT, or similar platforms in production or fundamentals of LLM architecture and optimization.
• Location requirement: must be onsite in New York, NY or Seattle, WA, USA.

Nice to have

• Expertise in foundation models, LLM fine-tuning, and customization for downstream tasks.
• Experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale.
• Knowledge of multi-modal modeling, few-shot learning, retrieval-augmented generation, or reinforcement learning from human feedback.
• Experience with online experimentation, A/B testing, and metrics design for advertising or e-commerce.
• Familiarity with computational advertising, auction theory, ad economics, and advertiser performance metrics.

Culture & Benefits

• Comprehensive health insurance including medical, dental, vision, and mental health support.
• 401(k) matching and paid time off including parental leave.
• Supportive and inclusive culture empowering employees to deliver best results.
• Opportunities for professional growth and mentorship.
• Work onsite in major US tech hubs with access to cutting-edge AI projects.