AmazonApplied Scientist II, Amazon Shipping
AI in this role
Lead an applied science team building large-scale machine learning forecasting and optimization systems.
As an Applied Scientist II, 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. 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.
Basic qualifications
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred qualifications
- Experience using Unix/Linux
- Experience in professional software development
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.
How we rate this
Applied Scientist II, Amazon Shipping at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where deep learning was part of your work. What did you do?
- Tell me about a project where optimization was part of your work. What did you do?
- Tell me about a project where forecasting was part of your work. What did you do?
- Tell me about a project where reinforcement learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Machine Learning, Deep Learning, Optimization, Forecasting, and Reinforcement Learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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