Sr Applied Scientist, Amazon Shipping
Amazon · Gurugram, India · Applied Science
senior
machine learning
Applied Scientist
ic
3+ yrs Master's
· Posted Feb 2, 2026
Skills
About this role
Amazon is hiring a senior-level Applied Scientist in the machine learning function based in Gurugram, India. The posting calls out experience with Python, Java, R, Spark and roughly 3+ years of relevant work. Listed education preference: a master's degree or equivalent.
- Role
- Applied Scientist
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Gurugram, India
- Experience
- 3+ years
- Education
- Master's degree
- Department
- Applied Science
- Posted
- Feb 2, 2026
AI Summary
Lead ML teams building large-scale forecasting and optimization systems for Amazon's transportation network. Set scientific direction, mentor applied scientists, and deliver production-grade ML solutions. Own end-to-end business metrics impacting customer experience and cost optimization.
More roles at Amazon
Delivery Trainer, RSR
Abbeville, LA · mid
Agile Compliance
Delivery Trainer, RSR
North Mankato, MN · mid
Agile Compliance
Operations Supervisor
Knuellwald, Germany · mid
Data Center Technician (Night Shift)
Mesa, AZ · mid
React AWS Networking
Data Center Technician (Night Shift)
Avondale, AZ · mid
React AWS Networking
All Amazon jobs →
Job description
from Amazon careersLead ML teams building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost.
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.
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.
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.
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
This is an excerpt. Read the full job description on Amazon careers →