Lead ML teams building large-scale forecasting and optimization systems that power Amazons global transportation network and directly impact customer experience and cost.
As an Applied Science Manager you will set scientific direction mentor applied scientists and partner with engineering and product leaders to deliver production-grade ML solutions at massive scale.
Key job responsibilities
1. Lead and grow a high-performing team of Applied Scientists providing technical guidance mentorship and career development.
2. Define and own the scientific vision and roadmap for ML solutions powering large-scale transportation planning and execution.
3. Guide model and system design across a range of techniques including tree-based models deep learning (LSTMs transformers) LLMs and reinforcement learning.
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.
5. Own end-to-end business metrics directly influencing customer experience cost optimization and network reliability.
6. Help contribute to the broader ML community through publications conference submissions and internal knowledge sharing.
A day in the life
Your day includes reviewing model performance and business metrics guiding technical design and experimentation mentoring scientists and driving roadmap execution. Youll 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 scientists or machine learning engineers management experience
- Knowledge of ML NLP Information Retrieval and Analytics
- Masters degree in engineering technology computer science machine learning robotics operations research statistics mathematics or equivalent quantitative field
- Experience building machine learning models or developing algorithms for business application
- Experience building complex software systems especially involving deep learning machine learning and computer vision that have been successfully delivered to customers
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