Applied Scientist, AWS Quick (AI)

TL;DR

Applied Scientist, AWS Quick (AI): Building next-generation models for intelligent automation with an accent on autonomous agents, API orchestration, and multimodal models. Focus on designing automated reasoning features, implementing scalable neural learning, and publishing research at peer-reviewed conferences.

Location: Must be based in Seattle (WA), Santa Clara (CA), or New York (NY)

Salary: $142,800 – $223,400 annually

Company

hirify.global Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform, serving everyone from startups to Global 500 companies.

What you will do

• Define and implement automated reasoning features using neural learning and symbolic/formal reasoning.
• Develop innovative solutions for autonomous agents, API orchestration, and multimodal models.
• Apply software engineering best practices to ensure a high standard of quality for all scientific deliverables.
• Conduct research and publish findings at top-tier peer-reviewed conferences and workshops.
• Partner with technology and business teams to drive data-driven business decisions.

Requirements

• PhD or Master's degree in CS, CE, ML, or a related field.
• 3+ years of experience building models for business applications.
• Proven track record of patents or publications at top-tier peer-reviewed journals or conferences.
• Proficiency in Python, Java, C++, or similar languages.
• Strong expertise in algorithms, data structures, numerical optimization, or distributed computing.
• Must be authorized to work in the US and located in specified office hubs.

Culture & Benefits

• Inclusive team culture with employee-led affinity groups and diversity events.
• Robust mentorship programs and extensive resources for professional career growth.
• Commitment to work-life harmony and flexibility.
• Comprehensive benefits package including health insurance, 401(k) matching, and parental leave.
• Competitive compensation including sign-on payments and Restricted Stock Units (RSUs).