Role at a glance
- Job function
-
AI & Data AI Research & Applied Science
- Salary
- Not yet verified Check the description for pay details; an amount or pay period has not been verified.
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Experience
- Senior Level Basic Qualifications - 5+ 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 - Demonstrated experience with generative AI and LLMs — fine-tuning, prompting, retrieval, or post-training. Preferred Qualifications - PhD, or a PhD or equivalent research experience and experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience in automation or monitoring frameworks, deployment or development - Experience designing evaluation frameworks for open-ended or subjective tasks where ground truth is expensive or unavailable, including synthetic data generation. - Experience with agentic and multi-turn systems, including RL-based post-training (RLHF/RLAIF/GRPO or similar), environment simulation, or agent harness evaluation.
- Education
- PhD, or Master's degree and 6+ years of applied research experience
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Role Summary
The Senior Applied Scientist researches and develops agentic AI technology for Amazon Connect, taking science solutions from conception through deployment. The role also owns the evaluation approach for agentic systems, using metrics and experiments to assess their quality and customer outcomes.
What You'll Do
- Analyze large datasets and conduct research to address complex business problems.
- Develop science solutions and agentic systems from conception through deployment.
- Define offline evaluation harnesses and online experiments to measure system performance.
- Identify trustworthy metrics that connect model quality with customer outcomes.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required: 5+ years building machine learning models for business applications; a PhD, or a Master's degree and 6+ years of applied research experience; programming experience in Java, C++, Python, or a related language; and generative AI and LLM experience in fine-tuning, prompting, retrieval, or post-training.
Required
- 5+ 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
- Demonstrated experience with generative AI and LLMs — fine-tuning, prompting, retrieval, or post-training.
Preferred
- PhD, or a PhD or equivalent research experience and experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in automation or monitoring frameworks, deployment or development
- Experience designing evaluation frameworks for open-ended or subjective tasks where ground truth is expensive or unavailable, including...
- Experience with agentic and multi-turn systems, including RL-based post-training (RLHF/RLAIF/GRPO or similar), environment simulation,...
Original job description
Content provided by the employer
Original job description
Content provided by the employer
As a Sr. Applied Scientist on our team, you will work closely with senior technical and business leaders from within the team and across AWS. You distill insight from huge data sets, conduct cutting-edge research, and develop science solutions to conquer complex business problems, from conception to deployment. You own the measurement science behind your work — defining the offline evaluation harnesses and online experiments that prove an agentic system is actually better, and converging on a small number of trustworthy metrics that tie model quality to customer outcomes. You have a strong academic background and industry experience in machine learning and deep learning, with deep domain knowledge in generative AI and LLMs. You are comfortable quickly prototyping and iterating on your ideas to build and evaluate robust agentic systems using modern tooling such as PyTorch, vLLM, agent frameworks and MCP, and AWS services including Amazon Bedrock and SageMaker.
Learn more about Amazon Connect here: https://aws.amazon.com/connect/
About the team
Our team is leading AI/ML research and development in Amazon Connect. We use state-of-the-art science and engineering practices to address the hard problems in contact center for our customers, and we move fast to implement solutions and refine them based on customer feedback.
Basic Qualifications
- 5+ 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
- Demonstrated experience with generative AI and LLMs — fine-tuning, prompting, retrieval, or post-training.
Preferred Qualifications
- PhD, or a PhD or equivalent research experience and experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience in automation or monitoring frameworks, deployment or development
- Experience designing evaluation frameworks for open-ended or subjective tasks where ground truth is expensive or unavailable, including synthetic data generation.
- Experience with agentic and multi-turn systems, including RL-based post-training (RLHF/RLAIF/GRPO or similar), environment simulation, or agent harness evaluation.
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.
The base salary range for this position is listed below. 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. 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.
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.