Tailored Management
Machine Learning Engineer
Tailored Management, Burlingame, California, United States, 94012
Job Title:
Machine Learning Engineer/Scientist Job ID : 59022-1 Pay : $80-$90/hour Location:
Burlingame, CA (Fully onsite) Duration:
9-month contract starting M-F, full-time (40 hours); W2, *Opportunity for extension or conversion based on performance and business needs* Health Benefits (Medical, Dental, Vision) + PTO
Description We are seeking a highly skilled and motivated ML Engineer/Scientist to join our 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 our 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 Qualification:
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 Qualification:
Master's or PhD degree in Computer Science, Electrical Engineering, or similar eld 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 ne-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
Must-Have Skills
1
2+ years of experience developing and evaluating ML/CV models
2
2+ years of experience developing ML pipelines (e.g., dataset preprocessing, model experimentation and evaluation, software integration, and real-time deployment)
3
3+ years of experience coding with Python
Nice-to-have Skills
1
Experience working with data from physical sensing technologies (e.g., cameras, physiological sensors, electromyography, lidar, radar, IMU)
2
Self-Supervise learning or Semi- supervise learning
3
Sensor Fusion
Machine Learning Engineer/Scientist Job ID : 59022-1 Pay : $80-$90/hour Location:
Burlingame, CA (Fully onsite) Duration:
9-month contract starting M-F, full-time (40 hours); W2, *Opportunity for extension or conversion based on performance and business needs* Health Benefits (Medical, Dental, Vision) + PTO
Description We are seeking a highly skilled and motivated ML Engineer/Scientist to join our 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 our 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 Qualification:
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 Qualification:
Master's or PhD degree in Computer Science, Electrical Engineering, or similar eld 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 ne-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
Must-Have Skills
1
2+ years of experience developing and evaluating ML/CV models
2
2+ years of experience developing ML pipelines (e.g., dataset preprocessing, model experimentation and evaluation, software integration, and real-time deployment)
3
3+ years of experience coding with Python
Nice-to-have Skills
1
Experience working with data from physical sensing technologies (e.g., cameras, physiological sensors, electromyography, lidar, radar, IMU)
2
Self-Supervise learning or Semi- supervise learning
3
Sensor Fusion