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# Senior ML Data Scientist - Wireless People Sensing

- **Company:** Algorized Inc
- **Location:** Campbell, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Python (Programming Language), Machine Learning, NumPy, SciPy, Sensor Fusion, Wireless Sensor Networks, Signal Processing, Pytorch, Autoscaling, Scikit Learn, Information Technology, Machine Learning Operations, Feature Extraction, Lidar
- **Published:** November 12, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-ml-data-scientist-wireless-people-sensing-campbell-ca--5e3de96d-5ef2-491e-8695-d3d61a8ff950

## About the Role

Data Science, Wireless Communications, Artificial Intelligence (AI), Wireless Communications, Startup, Data Science, Product Development, Signal Processing, Autoscaling, Algorithms, * PhD in Data Science, Computer Science, Wireless Communication, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field.

 * At least 3 years of hands-on experience developing machine-learning or data-science solutions for real-world applications.
 * Proven expertise in data science and machine learning, with experience applying statistical and learning-based methods to sensor or time-series data.
 * Strong knowledge of signal-processing principles and practical experience applying methods such as spectral analysis, filtering, estimation, detection, tracking, or sensor fusion.
 * Strong understanding of machine-learning fundamentals, including model development, evaluation, optimization, and generalization.
 * Strong Python skills and practical experience with frameworks such as PyTorch, scikit-learn, NumPy, and SciPy.
 * Ability to take ownership of open-ended technical problems and move effectively from exploration to validated solutions.
 * Excellent collaboration and communication skills, with genuine enthusiasm for solving challenging people-sensing problems., * Experience with radar, RF sensing, LiDAR, computer vision, acoustics, or other sensing modalities.
 * Experience designing experiments and working with complex, noisy, or imperfect real-world data.
 * Familiarity with self-supervised learning, representation learning, multimodal models, or foundation-model development.
 * Experience with 3D positioning, occupancy sensing, human activity recognition, tracking systems, or vital-sign estimation.
 * Familiarity with edge-AI constraints and the trade-offs involved in moving models from research into production.
 * Experience collaborating across data science, embedded, software, and product teams.

## Description

* Design, develop, and improve machine-learning models and algorithms for wireless people sensing using radar and other sensor signals.
 * Play a key role in developing foundational models that can support multiple people-sensing tasks, environments, and sensor configurations.
 * Develop signal-processing, machine-learning, and deep-learning methods that transform wireless sensor signals into accurate and robust people-sensing outputs.
 * Design model architectures and learning approaches that capture spatial and temporal patterns in wireless sensor data.
 * Design experiments, define evaluation methodologies, and analyze model behavior, limitations, and generalization.
 * Evaluate and adapt relevant advances in time-series and representation learning to improve model accuracy, robustness, and generalization across environments and sensor configurations.
 * Collaborate cross-functionally with software engineers and MLOps on infrastructure development.
 * Mentor junior team members and contribute to the company's technical direction and data-science practices.