Wireless Science Manager, Device Connectivity

Overview

Come join the Device connectivity team in building the next generation of innovative wireless solutions that create a magical experience on our products and services. We actively engage in strategic initiatives, foster partnerships with industry and academia, and leverage foundational artificial intelligence and large language models to stay at the forefront of technological advancements.

• Build, mentor, and develop a high‑performing team of applied scientists, setting the technical bar through code reviews, design reviews, and hands‑on contributions while fostering a culture of scientific excellence, innovation, and operational rigor.
• Define and drive the AI/ML science roadmap for wireless solutions by developing a deep understanding of Amazon's Devices and Services offerings, translating complex business problems into well‑defined scientific challenges, identifying high‑risk and high‑impact technical directions, and guiding the team to deliver them from conception through production.
• Collaborate cross‑functionally with engineering, product, and business partners to drive ML development from research through optimization and onto production devices, aligning science investments with product goals while meeting on‑device performance, latency, and resource constraints.
• Balance exploratory research with production delivery timelines, ensuring the team maintains scientific rigor while meeting business commitments.
• Represent the team's AI innovations to both internal leadership and the external scientific community through leadership reviews, publications, patents, and conference presentations, providing clear articulation of science strategy, progress, and impact.

• 3+ years of experience managing scientists or machine‑learning engineers.
• Knowledge of machine‑learning approaches and algorithms.
• PhD or Master’s degree in a relevant field.
• Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations.
• Experience programming in Java, C++, Python or a related language.
• Experience with deep learning libraries such as PyTorch, Tensor Flow, MxNet.
• Research publications in computer vision, deep learning or machine learning at peer‑reviewed workshops, conferences, or journals.

• Experience building machine‑learning models or developing algorithms for business applications.
• Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers.
• Experience in developing and deploying large language models in production on GPUs, Neuron, TPU or other AI acceleration hardware.
• Experience with training and deploying machine‑learning systems to solve large‑scale optimizations or providing technical support.
• Experience developing products for volume production.
• Experience conducting research in a corporate setting.
• Experience with tools such as PyTorch, Tensor Flow, ONNX, TFLite, scikit‑learn, numpy, scipy or edge inference frameworks.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.