Senior ML Data Scientist - Wireless People Sensing

Lever, Inc.; Campbell (CA); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Equity

Medical/Dental/Vision

401(k)

Unlimited PTO

Job summary

Algorized is hiring a Senior Data Scientist for on-site work in Campbell, CA. The role focuses on designing and deploying ML models for wireless people sensing using radar and other signals, and building foundational models to support multiple tasks and sensor configurations.

You will work across data science, signal processing, and product development, mentor teammates, and contribute to the company’s technical direction.

Qualifications

• PhD in a quantitative field or equivalent
• At least 3 years hands-on ML/data-science for real-world apps
• Proven ML/data-science expertise with sensor/time-series data
• Strong knowledge of signal-processing principles and methods
• Strong Python skills with PyTorch, scikit-learn, NumPy, SciPy
• Ability to tackle open-ended problems and derive validated solutions
• Excellent collaboration and communication skills

Responsibilities

• Design and improve ML models for wireless people sensing
• Develop foundational models for multiple sensing tasks and sensors
• Create signal-processing and ML methods to transform sensor signals into robust outputs
• Design architectures that capture spatial and temporal patterns
• Plan experiments, define evaluation methods, analyze model behavior
• Evaluate state-of-the-art methods for robustness across environments
• Collaborate with software engineers and MLOps on infrastructure
• Mentor junior team members and guide technical direction

Skills

Python

PyTorch

Signal processing

Time-series analysis

Research

Collaboration

Education

PhD in Data Science/CS/EE/Mathematics/Physics

3+ years industry experience

Tools

NumPy

SciPy

scikit-learn

Job description

Join Us in Building the Nervous System for Physical AI

Algorized is a VC-funded Silicon Valley deep-tech company with Swiss roots. We build edge-AI models that give robots real-time awareness of people using existing wireless sensors, enabling safer human–machine collaboration.

As we continue to scale, we are looking for a Senior Data Scientist who is passionate about innovation, applied research, and turning complex sensing challenges into robust products. If you thrive in a dynamic startup environment, take ownership, and enjoy working across data science, signal processing, and product development, we would love to meet you.

This is an on-site position based in Campbell, CA, USA, or Etoy, Switzerland. Fully remote arrangements are not available.

RESPONSIBILITIES

• 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.

QUALIFICATIONS

Minimum Requirements

• 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.

Preferred Requirements

• 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.

Algorized is an early‑stage startup, which means your equity matters. Every offer pairs a competitive salary with real ownership, plus medical, dental, and vision coverage, a 401(k), and unlimited PTO.