Part-Time Machine Learning/Signal Processing Engineer (Hybrid) We are seeking a part-time Machine Learning/Signal Processing Engineer to join our team. The role focuses on processing sensor signals, addressing noise challenges, and applying advanced time series modeling techniques such as Kalman Filter, LSTM, or GMM to understand the signal’s behavior over time. You will also develop algorithms to detect and analyze spatial phenomena within the signal. Responsibilities:
* Process and analyze sensor data with attention to noise management.
* Apply advanced time series modeling techniques (Kalman Filter, LSTM, GMM) to assess signal behavior over time.
* Develop statistical algorithms for spatial signal detection.
* Collaborate with our team to refine and implement solutions. Qualifications:
* At least 3 years of experience in signal processing and machine learning.
* Expertise in noise filtering and time series modeling techniques.
* Proficient in Kalman Filter, LSTM, or GMM for temporal data analysis.
* Familiarity with sensor data processing.
* Strong programming skills (Python or equivalent).
* Excellent problem-solving abilities and attention to detail. Location : Remote Type : Part-time Start date : ASAP Location: Modiin- Hybrid
* Process and analyze sensor data with attention to noise management.
* Apply advanced time series modeling techniques (Kalman Filter, LSTM, GMM) to assess signal behavior over time.
* Develop statistical algorithms for spatial signal detection.
* Collaborate with our team to refine and implement solutions. Qualifications:
* At least 3 years of experience in signal processing and machine learning.
* Expertise in noise filtering and time series modeling techniques.
* Proficient in Kalman Filter, LSTM, or GMM for temporal data analysis.
* Familiarity with sensor data processing.
* Strong programming skills (Python or equivalent).
* Excellent problem-solving abilities and attention to detail. Location : Remote Type : Part-time Start date : ASAP Location: Modiin- Hybrid
Requirements:
None
None
This position is open to all candidates.