Wireless Science Manager, Device Connectivity

Amazon Amazon · Big Tech · Sunnyvale, CA · Applied Science

Manager for an applied science team focused on AI/ML for wireless connectivity and sensing in Amazon devices. The role involves leading scientists, defining the AI/ML roadmap, collaborating on ML development from research to production, and balancing research with delivery.

What you'd actually do

  1. 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.
  2. 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.
  3. 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.
  4. Balance exploratory research with production delivery timelines, ensuring the team maintains scientific rigor while meeting business commitments.
  5. 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.

Skills

Required

  • 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

Nice to have

  • 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

What the JD emphasized

  • pushing the boundaries of AI/ML in wireless connectivity and sensing
  • drive scientific innovation
  • define and drive the AI/ML science roadmap
  • drive ML development from research through optimization and onto production devices
  • Balance exploratory research with production delivery timelines
  • AI innovations

Other signals

  • leading a team of applied scientists
  • defining and driving the AI/ML science roadmap
  • collaborating cross-functionally to drive ML development from research through optimization and onto production devices
  • balancing exploratory research with production delivery timelines
  • representing the team's AI innovations to leadership and the external scientific community