Senior Applied Scientist, Selling Partner Support Engagement

Amazon; Seattle (WA); On-site; USD 167,100 - 226,100; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon in Seattle is seeking a Senior Applied Scientist to own end-to-end RL-based agent improvement systems, from problem formulation through production deployment and impact measurement.

You will design preference learning, reward modeling, and policy optimization for conversational agents, collaborating with teams across NLP, ML, and tools to deploy state‑of‑the‑art models. You will publish research and mentor junior scientists to raise the bar.

Qualifications

• 7+ years of applied research experience.
• 5+ years of building ML models for business applications.
• PhD or Master’s + 5 years of applied research.
• Proficient in Java, C++, Python or related language.
• Experience with neural deep learning methods.
• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, TensorFlow, NumPy, SciPy.
• Experience with design, wireframing, and prototyping tools.
• Experience leveraging generative AI tools to enhance workflow and craft prompts.

Responsibilities

• Own end-to-end research and development of RL-based agent systems from problem formulation to production deployment.
• Design approaches to preference learning, reward modeling, and policy optimization for conversational agents.
• Build and maintain evaluation frameworks for agent quality across usefulness, correctness, safety, and alignment.
• Collaborate with scientists across NLP, optimization, ML, and statistics.
• Partner with 10+ engineering teams to deploy models to production for sellers worldwide.
• Publish research at top venues and support it through mentorship and hiring.

Skills

Python

Java

C++

Machine learning

Reinforcement learning

NLP

TensorFlow

NumPy

Education

PhD

Master's + 5 yrs research

Tools

R

scikit-learn

Spark MLLib

MxNet

Tensorflow

NumPy

SciPy

Job description

Stellen-ID: 10442696 | Amazon.com Services LLC

Amazon's Selling Partner Support handles tens of millions of contacts annually worldwide. The Titans Science team is transforming this experience by building AI agents that autonomously resolve seller issues, learn from every interaction, and continuously improve with minimal human intervention. These agents reason, remember, and adapt — from understanding the seller's context and selecting the right solution, to routing contacts optimally, automating resolution end‑to‑end, and augmenting associates with AI when human judgment is needed. We do this in deep partnership with multiple engineering and product partners.

Senior Applied Scientist – Responsibilities

• Own end‑to‑end research and development of RL‑based agent improvement systems — from problem formulation through production deployment and impact measurement.
• Design novel approaches to preference learning, reward modeling, and policy optimization in the context of conversational agents operating over real‑world tools and APIs.
• Build and maintain evaluation frameworks that measure agent quality across multiple dimensions: helpfulness, correctness, safety, and alignment with operational standards.
• Collaborate with a team of scientists working on the forefront of Natural Language Understanding, Optimization, Machine Learning and Statistics.
• Partner with 10+ engineering teams to deploy models into production systems serving sellers worldwide.
• Publish research at top venues (NeurIPS, ICML, EMNLP, AMLC) and actively support it.
• Raise the scientific bar through rigorous peer review, mentorship of junior scientists, and contribution to hiring.

A Day in the Life

You read the latest research papers and implement novel techniques by building rapid prototypes using AI‑assisted coding tools, then taking what works from prototype to production. You collaborate closely with product managers and engineering teams to translate seller pain points into deployed science solutions. You influence leadership by bringing the state of the art to strategic decisions about where the organization invests, and you drive the science roadmap for your domain — identifying new research directions, proposing experiments, and making the case for what to build next. You mentor other scientists on the team, raising the bar on rigor and execution and get mentored by Principals across the org. Finally, you attend meetings with other Amazonians to stay connected to the seller experience by understanding the real problems sellers face so your models solve what actually matters.

About the Team

Titans Science is a growing team of scientists building the AI that powers Amazon's seller support experience. We operate in across capabilities such as Agentic Systems, Knowledge Retrieval & Query Understanding, and Content Intelligence & Automation, each owning distinct problem spaces but sharing evaluation infrastructure and research insights. We work backwards from business problems, deeply understanding the problem space and domain, defining gold‑standard datasets, success metrics, and guardrails. This lets us run parallel experiments, compare approaches rigorously, and ship the best Science models to production. We publish at internal conferences and external venues, and we actively invest in research that compounds over multiple product cycles.

The team sits in Seattle and operates with high autonomy. Scientists own their domains end‑to‑end, from problem framing through production deployment. We value speed over perfection, scientific rigor over polish, and experimentation over debate. We value diverse experiences. Even if you do not meet all of the preferred qualifications listed above, we encourage you to apply. The team fosters an inclusive learning culture where individual growth is a priority — you will find mentorship, knowledge‑sharing, and career‑advancing resources here.

Qualifications

• 7+ years of applied research experience.
• 5+ years of building machine learning models for business application experience.
• PhD, or Master's degree and 5+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.
• Experience with modeling tools such as R, scikit‑learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience in a variety of design, wire‑framing, and prototyping tools.
• Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI‑generated outputs in a professional setting.
• Experience identifying opportunities to integrate AI solutions into products and services to drive business value.
• Building and Scaling Agentic System Components like Memory, Retrieval, Reasoning and Tool Calling.

Preferred Qualifications

• Experience with modeling tools such as R, scikit‑learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience in a variety of design, wire‑framing, and prototyping tools.
• Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI‑generated outputs in a professional setting.
• Experience identifying opportunities to integrate AI solutions into products and services to drive business value.
• Building and Scaling Agentic System Components like Memory, Retrieval, Reasoning and Tool Calling.

Benefits & Compensation

Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

The base salary range for this position is $167,100.00 – $226,100.00 USD annually and your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

Equal Opportunity Employment

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.