Wireless Science Manager, Device Connectivity

Description

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.

As a Applied Science Manager in the team, you will:

• 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.

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.

• 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, 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 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, 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.

Los Angeles County applicants:
Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position.

These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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