10 days ago
Tokyo, JapanStaff+
Responsibilities
- Advise and collaborate with APAC customers and partners on data management, machine learning workflows, and model deployment using Edge Impulse.
- Participate in sales and marketing activities, including events, client visits, presentations, and demonstrations.
- Collaborate with engineering and account management teams to design machine learning solutions and resolve technical challenges for intelligent devices.
- Develop data transformation, processing, training, and deployment code for machine learning models running on resource-constrained devices.
Requirements
- Bachelor's degree in engineering, information systems, computer science, data science, computer engineering, or a related technical field, or an equivalent higher degree.
- At least 4 years of relevant software applications engineering or software development experience with a bachelor's degree, 3 years with a master's degree, or 2 years with a PhD.
- At least 2 years of experience with programming languages such as C, C++, Java, or Python.
- At least 1 year of experience with debugging techniques.
- Experience developing embedded systems or cloud software, with exposure to Linux or real-time operating systems.
- Experience with machine learning and data analysis using libraries such as TensorFlow, Keras, PyTorch, NumPy, and Pandas.
- Experience developing, launching, or maintaining technical products in industrial, medical, automotive, IoT, or related markets.
- Demonstrated multidisciplinary problem solving, technical consulting, collaboration, leadership, and ability to work across domains and distributed teams in the APAC region.
- A master's degree is preferred.
About Qualcomm
Qualcomm is a public semiconductor company headquartered in San Diego, founded in 1985, that designs and sells wireless chipsets and platforms for mobile devices, automotive, IoT, and networking, notably the Snapdragon application processors and 5G modems. It also licenses a large portfolio of cellular patents to device makers, generating revenue alongside chip sales; its technology underpins many Android smartphones and emerging automotive and edge-compute systems, and it trades on NASDAQ as QCOM.