Description:
We are exploring and designing novel technologies for the next generation of AI and AR experiences. We are seeking a highly skilled and motivated ML Engineer/Scientist to join human-computer interaction (HCI) research team. We are looking for a candidate with strong coding skills and expertise in machine learning for time-series sensor data, computer vision (CV), software engineering, and/or hardware-software systems bring-up. The successful candidate will join multidisciplinary team to work on gesture recognition and multimodal machine learning using novel sensor technologies.
Responsibilities:
- Develop and benchmark machine learning and computer vision models for applications such as gesture recognition, hand pose estimation, object detection, contextual understanding, or physiological signal processing.
- Design and implement ML pipelines and systems that collect and preprocess datasets and enable algorithm experimentation.
- Enable multimodal data collection by developing experimental protocols for human-subjects research and bringing-up prototype wearable sensor software and hardware systems
- Collaborate across an interdisciplinary team of researchers and engineers to collect multimodal training datasets and to develop real-time interaction demos.
- Regularly report on project status, deliver high-quality code with thorough documentation, and effectively communicating updates through presentations and written reports
Minimum Qualifications:
- 2+ years of experience developing and evaluating ML/CV models
- 2+ years of experience developing ML pipelines (e.g., dataset preprocessing, model experimentation and evaluation, software integration, and real-time deployment).
- 3+ years of experience coding with Python
- Experience working with data from physical sensing technologies (e.g., cameras, physiological sensors, electromyography, lidar, radar, IMU)
- Bachelor's degree in Computer Science, Electrical Engineering, or related area, or equivalent practical experience
Preferred Qualifications:
- Master’s or PhD degree in Computer Science, Electrical Engineering, or similar fie
- Experience in computer vision, multimodal representation learning, self-supervised learning, semi-supervised learning, few-shot learning, multi-task learning, transfer learning, sensor fusion, or other advanced ML/CV techniques.
- Experience with integrating multimodal representation learning models with Large Language Models (LLMs) and fine-tuning larger systems for specific downstream applications, such as activity recognition, image captioning, or question answering.
- Experience developing data collection protocols to collect high quality diverse sensor datasets from humans
- Experience applying machine learning or other signal processing techniques to noisy sensor data in real-time human-computer interaction applications (e.g., cameras, EMG, IMU)
**This is a contract role for 6 months with possible extension**
