What are the responsibilities and job description for the Junior ML position at Algorized?
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.
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 have strong skills in statistics, probability, and machine learning/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.
- Good understanding of signal and image processing and ML techniques is a must.
- 1 years hands-on experience with Radar technologies (UWB / mmWave) and/or Wi-Fi or computer vision.
- Strong coding experience (test is required for this role).
- Startup mentality, solution-driven, can-do approach.
- Experienced in Algorithm design and optimization.
- Hands-on proficiency in C/C .
- Proficiency in Python and in standard ML tools – TensorFlow / PyTorch / Scikit-Learn.
- Experience with Generative Adversarial Neural Nets (GAN), time series models preferred.
- Ability to work in a hybrid mode with min. 60% in office.
Addition:
- Stock Options.
- 401(k).
- Health insurance.
- Dental insurance.
- Paid time off.
- Vision insurance.
