What you'd actually do

Lead the development of sophisticated AI solutions leveraging deep learning, LLMs, and advanced machine learning techniques to transform both seller operations and internal consultancy capabilities at scale

Define and drive long-term scientific vision for the organization, translating complex business challenges into innovative technical solutions that advance the state-of-the-art in applied machine learning

Design and implement advanced ML architectures combining multiple learning paradigms - from reinforcement learning and causal inference to predictive modeling - to tackle critical marketplace challenges

Architect next-generation recommendation and optimization systems that handle complex multi-dimensional constraints while maintaining robustness and interpretability at scale

Drive end-to-end development of AI applications from research through production, collaborating with engineering teams to ensure successful deployment and conducting rigorous A/B experiments to validate impact

Skills

Required

PhD, or a Master's degree and experience in building models for business application
Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
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 training and deploying machine learning systems to solve large-scale optimizations

Nice to have

Experience developing, deploying and managing AI products at scale
Track record of investigating, designing, and delivering innovative ML solutions that drive significant business impact

What the JD emphasized

autonomous drive scientific innovations

sophisticated AI solutions

LLMs

probabilistic modeling

optimization

prototyping and iterative improvement

bridging cutting models with real-world applications

scientific rigor

measurable business impact

deep learning

advanced machine learning techniques

transform both seller operations and internal consultancy capabilities at scale

long-term scientific vision

complex business challenges

innovative technical solutions

state-of-the-art in applied machine learning

advanced ML architectures

multiple learning paradigms

reinforcement learning

causal inference

predictive modeling

critical marketplace challenges

next-generation recommendation and optimization systems

complex multi-dimensional constraints

robustness and interpretability at scale

end-to-end development of AI applications

research through production

rigorous A/B experiments

Pioneer novel applications of foundation models and generative AI

sophisticated evaluation frameworks

Amazon's high standards for accuracy and reliability

technical discussions across organizational boundaries

communicating complex scientific concepts to diverse stakeholders

forefront of ML/AI research advancements

Experience developing, deploying and managing AI products at scale

innovative ML solutions that drive significant business impact

Other signals

Develop sophisticated AI solutions

Translate theoretical advances into practical applications

Drive end-to-end development of AI applications from research through production

Pioneer novel applications of foundation models and generative AI

Develop advanced ML architectures combining multiple learning paradigms

Amazon Strategic Account Services (SAS) Tech Organization is looking for an Applied Scientist Applied Scientist who can autonomously drive scientific innovations from research to production, developing sophisticated AI solutions that serve both Amazon's global seller base and internal Marketplace Consultants. Working in a highly collaborative environment, you'll leverage expertise in machine learning, operations research, and statistics to translate theoretical advances in LLMs, probabilistic modeling, and optimization into practical applications. The role demands strong capabilities in prototyping and iterative improvement, bridging cutting models with real-world applications while maintaining scientific rigor and measurable business impact.

Key job responsibilities

Lead the development of sophisticated AI solutions leveraging deep learning, LLMs, and advanced machine learning techniques to transform both seller operations and internal consultancy capabilities at scale
Define and drive long-term scientific vision for the organization, translating complex business challenges into innovative technical solutions that advance the state-of-the-art in applied machine learning
Design and implement advanced ML architectures combining multiple learning paradigms - from reinforcement learning and causal inference to predictive modeling - to tackle critical marketplace challenges
Architect next-generation recommendation and optimization systems that handle complex multi-dimensional constraints while maintaining robustness and interpretability at scale
Drive end-to-end development of AI applications from research through production, collaborating with engineering teams to ensure successful deployment and conducting rigorous A/B experiments to validate impact
Pioneer novel applications of foundation models and generative AI, developing sophisticated evaluation frameworks while maintaining Amazon's high standards for accuracy and reliability
Lead technical discussions across organizational boundaries, effectively communicating complex scientific concepts to diverse stakeholders while staying at the forefront of ML/AI research advancements

About the team What is Amazon Strategic Account Services (SAS)? The SAS team aims to accelerate the full potential of our Sellers, helping them to navigate the increasing complexity of the e-commerce space. Our team provides in-depth strategic consultancy using a data-driven, collaborative, and a Customer-focused approach to achieve commercial goals of Amazon Sellers.

Basic Qualifications

PhD, or a Master's degree and experience in building models for business application
Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
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 training and deploying machine learning systems to solve large-scale optimizations

Preferred Qualifications

Experience developing, deploying and managing AI products at scale
Track record of investigating, designing, and delivering innovative ML solutions that drive significant business impact

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.

Key job responsibilities

Lead the development of sophisticated AI solutions leveraging deep learning, LLMs, and advanced machine learning techniques to transform both seller operations and internal consultancy capabilities at scale
Define and drive long-term scientific vision for the organization, translating complex business challenges into innovative technical solutions that advance the state-of-the-art in applied machine learning
Design and implement advanced ML architectures combining multiple learning paradigms - from reinforcement learning and causal inference to predictive modeling - to tackle critical marketplace challenges
Architect next-generation recommendation and optimization systems that handle complex multi-dimensional constraints while maintaining robustness and interpretability at scale
Drive end-to-end development of AI applications from research through production, collaborating with engineering teams to ensure successful deployment and conducting rigorous A/B experiments to validate impact
Pioneer novel applications of foundation models and generative AI, developing sophisticated evaluation frameworks while maintaining Amazon's high standards for accuracy and reliability
Lead technical discussions across organizational boundaries, effectively communicating complex scientific concepts to diverse stakeholders while staying at the forefront of ML/AI research advancements

Basic Qualifications

PhD, or a Master's degree and experience in building models for business application
Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
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 training and deploying machine learning systems to solve large-scale optimizations

Preferred Qualifications

Experience developing, deploying and managing AI products at scale
Track record of investigating, designing, and delivering innovative ML solutions that drive significant business impact

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