ML/Data Scientist
About the Company
A variety of soft skills and experience may be required for the following role Please ensure you check the overview below carefully.
Algorized is a fast-growing deep tech startup building software platform for people positioning and sensing. We leverage algorithms and edge-ML with any market available communication sensors such as Ultra-Wideband Radar for accurate people tracking, positioning, vital sign detection (breathing, heart-rate), age classifications.
As we continue to rapidly expand, we are seeking a highly skilled Data Scientist with genuine passion for innovation and experience in developing products from concept to mass deployment.
If you are resourceful and have a good grasp of statistics, probability and ML / AI and are ready to join a dynamic fast-growing start-up this unique opportunity is for you!
Key Responsibilities
- Design and implement complex machine learning models and algorithms processing raw radar sensor data
- Design tools for data generation and collection from a single radar source and for fusing data from multiple sensors
- Manage the machine learning pipeline, including data collection, preprocessing, development, evaluation, and deployment
- Analyze extensive datasets to identify trends and patterns, and preprocess data for enhanced model accuracy and efficiency of people sensing and tracking
- Build the foundation for platform-based data collection and analytics
- Collaborate with cross-functional teams to integrate data analytics and ML pipeline with the rest of the SW stack on the edge
Minimum Requirements
- MSc / PhD in Data Science, Mathematics, Computer Science or a related field
- 4+ years hands on experience in a similar position (Radar / LiDAR / Computer vision)
- Strong ML research background in conjunction with a strong coding experience
- Startup mentality, solution driven, can do approach
- Proficiency in Python and in standard ML tools TensorFlow / PyTorch / Scikit-Learn
- Proficiency in C / C++
- Obsessively passionate and inquisitive and seek to solve everyday problems in innovative ways
- Experience with lightweight / edge ML technologies preferred
- Good understanding of signal and image processing preferred
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