Wireless AI/ML Science Manager

Amazon; Sunnyvale (CA); On-site; USD 211,000 - 286,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon is hiring an Applied Science Manager to lead a high-performing team of scientists and engineers focused on wireless AI/ML on devices. You will shape the science roadmap, translate business problems into scientific challenges, and guide projects from conception to production.

The role requires deep ML knowledge, strong leadership, and experience bringing models to on-device deployment with latency and resource constraints. This is a full-time on-site position in Sunnyvale, CA.

Qualifications

• 3+ years of scientists or machine learning engineers management experience.
• Knowledge of machine learning approaches and algorithms.
• PhD, or Master's degree.
• Experience with full software/hardware/networks development lifecycle.
• Experience programming in Java, C++, Python or related language.
• Experience with deep learning libraries such as PyTorch, TensorFlow, or MXNet.

Responsibilities

• Build, mentor, and develop a high-performing team of applied scientists.
• Define and drive the AI/ML science roadmap for wireless solutions.
• Collaborate cross-functionally to drive ML development from research to production.
• Balance exploratory research with production delivery timelines.
• Represent the team's AI innovations to leadership and external community.

Skills

Leadership experience

ML algorithms

Java

C++

Python

PyTorch

TensorFlow

Education

PhD, or Master's degree

Tools

ONNX

TFLite

scikit-learn

numpy

scipy

Job description

Amazon is hiring an Applied Science Manager to lead a high-performing team of scientists and engineers focused on wireless AI/ML on devices. You will shape the science roadmap, translate business problems into scientific challenges, and guide projects from conception to production.

The role requires deep ML knowledge, strong leadership, and experience bringing models to on-device deployment with latency and resource constraints. This is a full-time on-site position in Sunnyvale, CA.