Would you like to use your Machine Learning skills to solve real world problems and improve people’s lives? If you enjoy making a real impact on the business and the world, and you enjoy working on teams with other smart people, then we want to meet you. As a Machine Learning Research Co-op, we want you to help us develop the scientific insights and state of the art algorithms that will deliver positive change to our customers’. This is a unique opportunity to shape the experiences and technologies that millions of people will use.
Bose has a strong culture that is passionate about making things better, in terms of the products we build but also the way we work together, focusing on respect, integrity and excellence. We all work hard to develop innovative technologies that provide customers with life changing experiences. Our goal is helping people reach their fullest human potential, so they can feel more, do more, and be more.
- Plan and execute cutting-edge development to advance the state of the art in machine perception, mapping, reconstruction and localization, as well as 3D scene understanding across optical/inertial/acoustic sensing systems.
- Prototype novel algorithms for Sensor Fusion like IMU, RF, EXG etc. with optical tracking.
- Develop robust algorithms and systems for integrating multiple sensors and modalities.
- Build novel prototype capture system for offline and real-time online systems.
- Develop algorithms for optical tracking of hands, bodies and objects and their interactions using machine learning.
- Currently pursuing a MS/PhD degree in Computer Science or related STEM field with published projects in the fields of deep learning and computer vision in conferences.
- Must be available to start on or after 1st July 2019.
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
- Hands-on experience implementing 3D computer vision algorithms, Sensor Fusion, SLAM, Reconstruction, Mapping, Localization and Image Processing.
- Hands on experience with Machine Learning tools like scikit-Learn, XGBoost, pandas, SciPy, Matploltib.
- Hands on experience with Deep Learning frameworks like TensorFlow, Keras, PyTorch etc.
- Experience with real world system building and data collection, including design, coding (C++) and evaluation (C++/Python).
- Experience with model optimization for mobile [Android/iOS]/embedded platforms.
- Excellent communication and presentation skills, and the ability to explain deep technical results to diverse groups of stakeholders.
- A passion for solving hard, ill-defined problems, comfort with taking the initiative, and a life-long learner who continually seeks to improve their skills and understanding.
- Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.
Bose is an equal opportunity employer that is committed to inclusion and diversity. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status, or any other legally protected characteristics. For additional information, please review: (1) the EEO is the Law Poster (http://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf); and (2) its Supplements (http://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm). Please note, the company’s pay transparency is available at http://www.dol.gov/ofccp/pdf/EO13665_PrescribedNondiscriminationPostingLanguage_JRFQA508c.pdf. Bose is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the application or employment process, please send an e-mail to Wellbeing@bose.com and let us know the nature of your request and your contact information.
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- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1