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Applied Scientist II, Search Ranking, Search Ranking
Job Location:
Job Location:
Palo Alto, CA - USA
Yearly Salary:
USD 142800 - 193200
Yearly Salary:
Posted:
7 September 2026 (7 days ago)
Posted:
Application Deadline:
5 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
The Amazon Search team creates customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories Amazon Product Search services go to work. We design develop and deploy high-performance distributed search systems that rank a catalog of billions of products for hundreds of millions of shoppers.
The Search Relevance team owns the ranking models that decide the order of results on every Amazon search this role you will design and post-train deep ranking models including LLM-based rankers and multi-tower deep learning models that jointly optimize purchase relevance and personalization. You will invent modeling and training techniques that push the Pareto frontier across multiple objectives and take your work end to end from novel research prototype through offline evaluation to production online experimentation.
Personalization is a first-class objective on this team. You will build models that reason over each customers history durable preferences and query intent to decide which results best fit that specific customer rather than optimizing a single population-level ranking.
We treat search as an active research frontier and invest heavily in staying at the leading edge of ML. Beyond todays ranking stack our current explorations include LLM agents that reason and plan across multi-step workflows tool-augmented foundation models and new paradigms that combine retrieval reasoning and personalization. You will help chart where search goes next and see your ideas ship to real customers within weeks not quarters.
You will work in a dynamic entrepreneurial team while leveraging the resources of one of the worlds leading technology companies. Please visit for more information.
Key job responsibilities
Your responsibilities include but are not limited to:
- Design train and deploy state-of-the-art ranking models that decide how results are ordered on Amazon search spanning LLM-based rankers and multi-tower deep learning architectures that jointly model engagement relevance and personalization.
- Post-train LLMs and ranking models with supervised fine-tuning reinforcement learning (e.g. GRPO DPO RLHF) knowledge distillation and listwise ranking losses (e.g. LambdaLoss ListNet ListMLE).
- Compose multiple objectives (engagement relevance personalization) into a single ranking through principled multi-objective optimization at inference.
- Design large-scale label pipelines including LLM-as-teacher supervision that turn customer signals and expert judgment into training and reward signals.
- Optimize inference for production ranking models through quantization quantization-aware training teacher-student distillation and serving-stack tuning.
- Evaluate proposed solutions through offline benchmarks and online A/B tests and drive the analysis that decides whether a change ships.
- Publish and present your work at internal and external scientific venues in ML NLP and IR.
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing
- Experience with PyTorch JIT compilation and AOT tracing or experience with vLLM SGLang TensorRT or similar platforms in production environments
- Experience with Machine Learning and Large Language Model fundamentals including architecture training/inference lifecycles and optimization of model execution or experience leading and influencing your team or organization
- Experience with learning-to-rank and listwise ranking losses (LambdaLoss LambdaRank ListNet ListMLE ApproxNDCG).
- Experience designing large-scale online A/B tests and analyzing offline-to-online metric correlation.
- Publications in top ML NLP or IR venues (such as NeurIPS ICML ACL EMNLP SIGIR KDD WWW WSDM).
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees supervisors and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees supervisors and staff to ensure exceptional customer service; and follow all federal state and local laws and Company policies. Criminal history may have a direct adverse and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above as well as the abilities to adhere to company policies exercise sound judgment effectively manage stress and work safely and respectfully with others exhibit trustworthiness and professionalism and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The Search Relevance team owns the ranking models that decide the order of results on every Amazon search this role you will design and post-train deep ranking models including LLM-based rankers and multi-tower deep learning models that jointly optimize purchase relevance and personalization. You will invent modeling and training techniques that push the Pareto frontier across multiple objectives and take your work end to end from novel research prototype through offline evaluation to production online experimentation.
Personalization is a first-class objective on this team. You will build models that reason over each customers history durable preferences and query intent to decide which results best fit that specific customer rather than optimizing a single population-level ranking.
We treat search as an active research frontier and invest heavily in staying at the leading edge of ML. Beyond todays ranking stack our current explorations include LLM agents that reason and plan across multi-step workflows tool-augmented foundation models and new paradigms that combine retrieval reasoning and personalization. You will help chart where search goes next and see your ideas ship to real customers within weeks not quarters.
You will work in a dynamic entrepreneurial team while leveraging the resources of one of the worlds leading technology companies. Please visit for more information.
Key job responsibilities
Your responsibilities include but are not limited to:
- Design train and deploy state-of-the-art ranking models that decide how results are ordered on Amazon search spanning LLM-based rankers and multi-tower deep learning architectures that jointly model engagement relevance and personalization.
- Post-train LLMs and ranking models with supervised fine-tuning reinforcement learning (e.g. GRPO DPO RLHF) knowledge distillation and listwise ranking losses (e.g. LambdaLoss ListNet ListMLE).
- Compose multiple objectives (engagement relevance personalization) into a single ranking through principled multi-objective optimization at inference.
- Design large-scale label pipelines including LLM-as-teacher supervision that turn customer signals and expert judgment into training and reward signals.
- Optimize inference for production ranking models through quantization quantization-aware training teacher-student distillation and serving-stack tuning.
- Evaluate proposed solutions through offline benchmarks and online A/B tests and drive the analysis that decides whether a change ships.
- Publish and present your work at internal and external scientific venues in ML NLP and IR.
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing
- Experience with PyTorch JIT compilation and AOT tracing or experience with vLLM SGLang TensorRT or similar platforms in production environments
- Experience with Machine Learning and Large Language Model fundamentals including architecture training/inference lifecycles and optimization of model execution or experience leading and influencing your team or organization
- Experience with learning-to-rank and listwise ranking losses (LambdaLoss LambdaRank ListNet ListMLE ApproxNDCG).
- Experience designing large-scale online A/B tests and analyzing offline-to-online metric correlation.
- Publications in top ML NLP or IR venues (such as NeurIPS ICML ACL EMNLP SIGIR KDD WWW WSDM).
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees supervisors and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees supervisors and staff to ensure exceptional customer service; and follow all federal state and local laws and Company policies. Criminal history may have a direct adverse and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above as well as the abilities to adhere to company policies exercise sound judgment effectively manage stress and work safely and respectfully with others exhibit trustworthiness and professionalism and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.
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 for more information. If the country/region youre applying in isnt 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 CA Palo Alto - 171600.00 - 222200.00 USD annually
USA WA Seattle - 142800.00 - 193200.00 USD annually
Required Experience:
IC
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