Senior Applied Scientist

Amazon; Boston (MA); On-site; USD 167,100 - 226,100; Full time

Job summary

Amazon is seeking an Applied Scientist in Boston to drive innovations in Generative AI and multimodal understanding. You will formulate research problems, design advanced models, and oversee machine learning pipelines affecting millions of customers. Qualified candidates should hold a PhD or a Master's with significant applied research experience and be proficient in programming languages like Java, C++, or Python. The salary range is between $167,100.00 and $226,100.00 annually.

Qualifications

• 4+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Formulate novel research problems at the intersection of GenAI and multimodal learning.
• Design and implement leading models leveraging VLMs and foundation models.
• Own end-to-end ML pipelines from research ideation to production deployment.

Skills

Machine learning model building

Programming in Java, C++, Python

Neural deep learning methods

Statistical analysis

Education

PhD or Master's degree with 6+ years experience

Tools

Multimodal transformers

Job description

Amazon Selection and Catalog Systems (ASCS) – Applied Scientist

At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We are solving a fundamental AI challenge: establishing product identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog, covering billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity—from electronics to groceries to digital content.

The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data—while maintaining accuracy and trust for high‑stakes business decisions affecting millions of customers daily.

Key Responsibilities

• Formulate novel research problems at the intersection of GenAI, multimodal learning, and large‑scale information retrieval—translating ambiguous business challenges into tractable scientific frameworks
• Design and implement leading models leveraging VLMs, foundation models, and agentic architectures to solve product identity, relationship inference, and catalog understanding at billion‑product scale
• Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions
• Own end‑to‑end ML pipelines from research ideation to production deployment—processing petabytes of multimodal data with rigorous evaluation frameworks
• Define research roadmaps aligned with business priorities, balancing foundational research with incremental product improvements
• Mentor peer scientists and engineers on advanced ML techniques, experimental design, and scientific rigor—building organizational capability in GenAI and multimodal AI
• Represent the team in the broader science community—publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research

Basic Qualifications

• 4+ years of applied research experience
• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with training and deploying machine learning systems to solve large‑scale optimizations
• Prior experience in the domains of LLMs, foundation models, or large‑scale deep learning systems
• Publications in top‑tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, EMNLP, ACL, NAACL, COLING, KDD, SIGMOD, WWW, AAAI, or similar
• Experience with Visual Language Models (VLMs), multimodal transformers, or vision‑language pretraining
• Experience with explainable AI, model interpretability, or uncertainty quantification
• Strong experimental design skills and statistical analysis expertise
• Hands‑on experience with Generative AI, including prompt engineering, fine‑tuning, RLHF, or agentic architectures

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Salary range: 167,100.00 - 226,100.00 USD annually.

Location: USA, WA, Seattle