About the Company

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 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 and other sensor data to address customer business needs
• 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
• Analyze extensive datasets to identify trends and patterns and interpret them
• Design tools for synthetic data generation and algorithm validation
• Test and develop new techniques to provide critical insights and communicate them clearly with stakeholders 
• 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
• 1+ 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
• Experienced in Algorithm design and optimization
• Hands on 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
• Experience with Generative Adversarial Neural Nets (GAN) preferred
• Good familiarity time series models preferred
• Ability to work in a hybrid mode with min. 60% in office