Machine Learning Scientist
Are you fascinated by the infinite possibilities of cyber-physical systems? Do you dream of developing ambitious technologies that will bridge the physical and virtual world and define the future? Are you passionate about applying your expertise in your field of engineering or science? If the answer is yes, then the ASUS Robotics & AI Center is the perfect environment for you to thrive.
Our goal is to create a multidisciplinary team of the world’s brightest engineers and scientists to develop ambitious technologies that will define the future. If you have the passion, knowledge and expertise to contribute to an elite and diverse team of experts, we strongly encourage you to apply today.
Roles & responsibilities
- Work with other stakeholders to gain new insights from data by employing statistical and/or machine learning models.
- Employ fast experimentation, iterations, and exploratory data analysis to reduce time to market.
- Work with data-infrastructure engineers to build up top-notch data infrastructure and tools.
- Write clean, maintainable, and well-commented source code.
- Work in a cross-functional team that takes ownership of the full software lifecycle.
- Independently read relevant literature and share your insights and knowledge with other stakeholders.
- Collaborate with other teams to make optimal software architecture design decisions.
Qualifications
- Master’s degree or PhD in computer science, electrical engineering, mechanical engineering, applied mathematics, or a related field.
- Exceptional academic track record with expertise in data science, statistics, machine learning, and/or artificial intelligence.
- Expertise in deep learning frameworks such as TensorFlow and/or PyTorch. Hands-on experience with training deep learning models such as CNN, RNN, and/or graph NN. Familiarity with traditional machine learning models.
- Exceptionally strong understanding of fundamentals and problem solving skills.
- Strong verbal and written communication skills.
- Understanding of software development best practices, including coding standards, code reviews, design patterns, source control management, and test automation.
- Programming skills in C++, Python, JavaScript, and/or Go.