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Applied Scientist II, Amazon Shipping

Amazon · Hyderabad; Gurugram, India

About this role

Applied Scientist II on Amazon Shipping’s ML teams, building large-scale forecasting and optimization systems for Amazon’s global transportation network. The role sets scientific direction and delivers production-grade solutions intended to improve delivery reliability, customer experience and cost.

Responsibilities

  • Lead and develop a team of Applied Scientists through technical guidance, mentorship and career development. Define the scientific vision and roadmap for ML-based transportation planning and execution.
  • Guide model and system design using techniques that include tree-based models, deep learning (LSTMs and transformers), LLMs and reinforcement learning. Review model performance, business metrics and experiments, and ensure solutions are robust, interpretable, scalable and production-ready.
  • Partner with Product, Operations and Engineering leaders to support proactive decisions and corrective actions. Own business metrics affecting customer experience, costs and network reliability, while balancing near-term delivery with longer-term innovation.
  • Contribute to publications, conference submissions and internal knowledge sharing.

Basic qualifications: 3+ years of experience building models for business applications; a PhD, or a master’s degree plus 4+ years of experience in CS, CE, ML or a related field; patents or publications in top-tier peer-reviewed conferences or journals; programming experience in Java, C++, Python or a related language; and experience in at least one of algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.

Preferred qualifications

Experience with Unix/Linux and professional software development. The listed job locations are Hyderabad and Gurugram, India.

Skills for this role

Machine LearningForecastingOptimizationTree-based modelsDeep LearningLSTMsTransformersLarge Language ModelsReinforcement LearningModel evaluationExperimentationJavaC++PythonAlgorithmsData structuresParsingNumerical optimizationData miningParallel computingDistributed computingHigh-performance computingUnixLinuxSoftware developmentScientific publishingMentorship

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