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As aon theteam, you’ll gain applied data science experience, working on a team of data scientists and embedded software engineers on Artificial Intelligence and Machine Learning solutions across the client devices portfolio. In this role, you will be responsible for realizing CTO AI initiatives, implementing algorithms, working with data scientists, data, and embedded SW engineers to rapidly develop, and deploy AI-enabled solutions for millions of end users.
You will:
- Work with engineering teams to integrate and deploy AI applications on client devices with backend cloud integration
- Work across a diverse set of telemetry collection and deployment environments inclusive of client AI/ML frameworks, endpoint & real-time OSes, and embedded firmware ecosystems
- Develop AI/ML software solutions tailored for client silicon using strong knowledge of client device ecosystem nuances and complexities
- Conduct experiments to train, tune, and optimize Machine Learning / Deep Learning models for delivery onto client devices
- Translate business questions into compelling use cases and provide insights using data and statistical methods as well as tell stories using data; Advocate and execute strategies to adopt data and data science in all business and technical conclusions
Essential Requirements
- Master's degree or higher in AI/ML, Computer Science, Statistics, Mathematics, or other Engineering & Scientific fields with a significant quantitative component; Bachelors + 5 years, MS + 3 years minimum, or PhD.
- Some experience developing for Microsoft (MS) Windows OS including client Software Development Kits (SDKs), MS DirectML, WinML, MS Graph, and experience with embedded device development in at least one RTOS
- Solid knowledge of AI/ML optimization techniques for delivering models and algorithms into resource-constrained environments including the ability to deliver AI / ML algorithms using one or more of C, C++, and Microsoft C#/.NET as well as strong experience with Deep Learning libraries and runtimes such as PyTorch, TensorFlow, TensorRT, and nuances of their application in Client ecosystems
- Good communicator with the ability to understand analytical methods and algorithms with a solid understanding of Large/Small Language Models, Machine Learning, Deep Learning, and Generative AI.
- Experience working in software development or other cross-functional teams
Desirable Requirements
- Bachelor’s degree / Master’s degree, solid knowledge and application of engineering concepts along with effective problem-solving ability
- Familiarity with development in real-time embedded environments and experience working with Open Neural Network Exchange (ONNX) models and the ONNX run time (ORT) as well as experience with at least one major hardware vendor toolchain such as Intel OpenVino, Qualcomm QNN, NVIDIA CUDA, or AMD Ryzen AI Software