Applied Scientist, Amazon Selection and Catalog Systems (ASCS)

Amazon

San Francisco (CA)

On-site

USD 180,000 - 250,000

Full time

14 days+

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Job summary

Amazon’s Applied Scientist role in the ASCS group seeks bold researchers to advance GenAI, multimodal learning, and billion‑product catalog understanding. You will translate business challenges into rigorous ML problems and push state‑of‑the‑art models from concept to production.

Candidates typically hold PhD or a Master’s with 4+ years experience in CS/ML, are proficient in Java/C++/Python, and enjoy mentoring others, publishing findings, and shaping product‑level solutions at scale in a

Qualifications

  • PhD or Master’s degree with 4+ years in CS/CE/ML or related field.
  • Experience programming in Java, C++, Python or related language.

Responsibilities

  • Formulate novel research problems at GenAI, multimodal learning, and large-scale information retrieval.
  • Design and implement models using VLMs and foundation models for catalog understanding at billion‑product scale.
  • Pioneer explainable AI methodologies balancing performance with production requirements.
  • Own end-to-end ML pipelines from research ideation to production deployment.
  • Define research roadmaps aligned with business priorities and product improvements.
  • Mentor scientists and engineers on ML techniques, experimental design, and rigor.
  • Represent the team in the science community with talks and publications.

Skills

Java
C++
Python

Education

PhD
Master's degree

Job description

Applied Scientist, Amazon Selection and Catalog Systems (ASCS)

Job ID: 10480254 | Amazon.com Services LLC

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 infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're 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. The scale is staggering: 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.

Amazon's Item and Relationship Platform group is looking for an innovative and customer‑focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state‑of‑the‑art algorithms, models, and services to infer product‑to‑product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next‑generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers.

Key Job 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
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience programming in Java, C++, Python or related language
Preferred Qualifications
  • PhD
  • 2+ years of CS, CE, ML or related field experience
  • Have publications at top‑tier peer‑reviewed conferences or journals
  • Proven track record of successfully applying ML‑based solutions to complex problems in business, science, or engineering.

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

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