Junior ML & Signal Processing Engineer (Radar/Edge ML)
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 Junior ML and Signal Processing Engineer with genuine passion for innovation and product development with experience from software-on-edge design through product delivery to customers. If you are resourceful, have deep understanding in system architecture, edge-computing, embedded systems and ready to join a dynamic fast-growing start-up this unique opportunity is for you!
LOCATION
Hybrid/Campbell California US
EMPLOYMENT TYPE
Full Time
Responsibilities
Qualifications
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Design and implement complex machine learning models and algorithms processing raw radar sensor data and other sensor data to address customer business needs
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Manage the machine learning pipeline, own the process of gathering, extracting, and compiling data across sources via relevant tools and separately format, re-structure, or validate data to ensure quality, and review the datasets to ensure it is ready for analysis
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Analyze extensive datasets to identify trends and patterns and interpret them
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Design tools for synthetic data generation and algorithm validation. Test and develop new techniques to provide critical insights and communicate them clearly with stakeholders
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Preprocess data for enhanced model accuracy and efficiency of people sensing and tracking
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Build the foundation for platform-based data collection and analytics
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Collaborate with cross-functional teams to integrate data analytics and ML pipeline with the rest of the SW stack on the edge
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MSc/PhD in Data Science, Mathematics, Computer Science or a related field​
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1+ years hands on experience in a similar position (Radar / LiDAR / Computer vision)​
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Strong ML research background in conjunction with a strong coding experience​
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Startup mentality, solution driven, can do approach​
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Hands on proficiency in Python and in standard ML tools – TensorFlow / PyTorch / Scikit-Learn / C/C++​
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Experienced in Algorithm design and optimization​​
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Obsessively passionate and inquisitive and seek to solve everyday problems in innovative ways​
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Experience with lightweight / edge ML technologies preferred​
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Good understanding of signal and image processing preferred
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Experience with Generative Adversarial Neural Nets (GAN) preferred
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Good familiarity time series models preferred
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Ability to work in a hybrid mode with min. 60% in office