Lead ML teams building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost.<br/><br/>As an Sr Applied Scientist, you will set scientific direction, mentor applied scientists, and partner with engineering and product leaders to deliver production-grade ML solutions at massive scale.<br/><br/>Key job responsibilities<br/>1. Lead and grow a high-performing team of Applied Scientists, providing technical guidance, mentorship, and career development.<br/>2. Define and own the scientific vision and roadmap for ML solutions powering large-scale transportation planning and execution.<br/>3. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning.<br/>4. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions.<br/>5. Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability.<br/>6. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing.<br/><br/>A day in the life<br/>Your day includes reviewing model performance and business metrics, guiding technical design and experimentation, mentoring scientists, and driving roadmap execution. You’ll balance near-term delivery with long-term innovation while ensuring solutions are robust, interpretable, and scalable. Ultimately, your work helps improve delivery reliability, reduce costs, and enhance the customer experience at massive scale.
- 3+ years of building machine learning models for business application experience<br/>- PhD, or Master's degree and 6+ years of applied research experience<br/>- Experience programming in Java, C++, Python or related language<br/>- Experience with neural deep learning methods and machine learning
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.<br/>- Experience with large scale distributed systems such as Hadoop, Spark etc.<br/><br/>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 <a href="https://amazon.jobs/content/en/how-we-hire/accommodations">https://amazon.jobs/content/en/how-we-hire/accommodations</a> for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Source: Amazon careers — Read the original posting and apply
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