Wireless Science Manager, Device Connectivity

Amazon.com, Inc.
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Tech stack

Mxnet
Java
Artificial Intelligence
Computer Vision
C++
Code Review
Data Mining
Information Retrieval
Python
Machine Learning
Natural Language Processing
NumPy
TensorFlow
SciPy
Software Engineering
Graphics Processing Unit (GPU)
PyTorch
Large Language Models
Deep Learning
Scikit Learn
ONNX (Open Neural Network Exchange) Format
Build Process
Machine Learning Operations
Software Coding
Software Version Control

Job description

  • 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.

Requirements

  • 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, * 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

Benefits & conditions

The base salary range for this position is 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. Amazon also 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.

About the company

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.

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