Wireless Science Manager, Device Connectivity

About the role

Come join the Device connectivity team in building the next generation of innovative wireless solution that create a magical experience on our products and services. We actively engage in strategic initiatives, foster partnerships with industry and academia, leverage foundational artificial intelligence and large language models to stay at the forefront of the technological advancements. We are seeking an experienced Applied Science Manager to lead and grow a team of applied scientists who are pushing the boundaries of AI/ML in wireless connectivity and sensing. In this role, you will combine deep technical expertise with strong people leadership to drive scientific innovation that directly impacts millions of customers worldwide.

Key job responsibilities

• 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 your 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.

About the team

Device Connectivity team is empowering possibilities through wireless innovation on our devices and through services, our vision is to design and develop transformative products and services that consistently exceed our customers' expectations.

Basic Qualifications

• 3+ years of scientists or machine learning engineers management experience
• Knowledge of machine learning approaches and algorithms
• PhD, or Master's degree
• 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 related language
• Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet
• Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals

Preferred Qualifications

• 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
• Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience in machine learning, data mining, information retrieval, statistics or natural language processing
• Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience in development or technical support
• Experience developing products for volume production
• Experience with conducting research in a corporate setting
• Experience with tools such as PyTorch, TensorFlow, ONNX, TFLite, scikit-learn, numpy, scipy or edge inference frameworks

Pay

USA, CA, Sunnyvale - 211,400.00 - 286,000.00 USD annually. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

Benefits

Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

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