Applied Scientist I, Amazon Shipping
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Recruiter screen and (for most SDE roles) an online assessment, one technical phone screen, then a single-day interview loop of four to six 45–60 minute sessions mixing coding, system design, and Leadership-Principle behavioral rounds. A Bar Raiser from outside the hiring team joins the loop and can veto the hire.
Read the full Amazon interview process →Description
Building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost.
Key job responsibilities
1. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning.
2. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders.
3. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions.
4 Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability.
5. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing.
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Have publications at top-tier peer-reviewed conferences or journals
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
1. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning.
2. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders.
3. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions.
4 Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability.
5. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing.
Basic Qualifications
- Experience programming in Java, C++, Python or related language- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
Preferred Qualifications
- Experience implementing algorithms using both toolkits and self-developed code- Have publications at top-tier peer-reviewed conferences or journals
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.
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