New job, posted less than a week ago!
Job Details
Posted date: Apr 29, 2025
Location: Austin, TX
Estimated salary: $205,200
Range: $150,400 - $260,000
Description
The SCOT-SIA (Science, Intelligence and Analytics) team is seeking an Applied Scientist III to lead the development and implementation of AI/ML models that will transform labor planning and execution across Amazon's Supply Chain operations. You will drive the scientific vision for next-generation intelligent automation systems that enhance decision-making, optimize resource allocation, and improve operational efficiency throughout our vast fulfillment networks across the world.In this role, you will tackle intrinsically hard, previously unsolved problems in labor planning and execution. You will invent new scientific techniques and paradigms to address complex customer needs and business challenges at a product level. Your work will focus on developing and implementing state-of-the-art large language models, natural language processing, and generative AI solutions to create more intelligent, automated, and user-friendly systems that revolutionize how we plan and execute our operations.
We are looking for a passionate and experienced scientist who can lead and mentor a team, collaborate effectively across organizations, and drive innovation that delivers significant business impact. You will work closely with technical and business partners to translate complex scientific concepts into practical solutions that delight our customers and optimize our operations.
Key job responsibilities
* Lead the design, development, and implementation of novel AI/ML models and algorithms for labor planning, forecasting, and execution optimization
* Drive the scientific vision for intelligent automation systems, identifying key challenges and proposing innovative solutions that advance the state of the art
* Collaborate with cross-functional teams to integrate AI solutions into production systems, ensuring scalability, reliability, and performance
* Mentor junior scientists and engineers, fostering a culture of scientific excellence and innovation
* Influence product strategy and roadmaps through data-driven insights and scientific expertise
* Develop and implement responsible AI practices, including explainable AI techniques and ethical considerations
* Contribute to the broader scientific community through publications, patents, and conference presentations, when aligned with business objectives
About the team
SCOT SIA (Science, Intelligence, & Analytics) serves as the research, automation, and insight arm of the Planning & Execution team of NA Supply Chain org. SIA identifies technical gaps, analytical opportunities, and complex operational and planning trends within NACF, in order to action them strategically and sustainably.
SIA Science team is the science wing of SIA that specifically focuses on the creation, improvement, and automation of labor planning models and processes. This is achieved through AI and ML modeling, scientific analysis of existing processes, and optimization techniques. Science team partners with tech & non-tech partners to improve existing tech solutions and provide data driven recommendations for strategic model implementations.
Qualifications
- PhD in Computer Science, Machine Learning, or a related field- 5+ years of industry or post-PhD experience in applied machine learning, with a focus on NLP, LLMs, or generative AI
- Strong publication record in top-tier peer-reviewed AI/ML conferences or journals
- Demonstrated experience building and deploying production-grade AI systems, including prompt engineering, AI agent development, and LLM optimization
- Expertise in designing and implementing end-to-end AI-ML systems, from data processing to model deployment
- Proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow
- Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences
- Demonstrated ability to lead technical projects and mentor junior team members
Extended Qualifications
- Experience with AWS AI/ML services and cloud computing architectures- Familiarity with supply chain optimization or workforce management problems
- Track record of delivering AI/ML solutions that have driven significant business impact
- Experience with explainable AI techniques and responsible AI practices
- Familiarity with retrieval augmented generation (RAG) and other advanced LLM techniques
- Contributions to open-source ML projects or development of internal ML platforms
- Experience collaborating with product managers and business stakeholders to define and prioritize ML initiatives
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Check out other jobs at Amazon.