Principal Engineer – Time-series & Sensor Reasoning Models (lorenz Labs)

Analog Devices Foundation

Multiple Locations
$170,775 to $256,163; discretionary performance-ba...
On-site
Time-series foundation models
Multi-sensor data integration
Compact model architectures
Analog Devices is seeking a Principal Engineer for their Lorenz Labs division, focusing on Time-Series and Sensor Reasoning Models. The role involves developing advanced AI models that integrate multimodal sensor data for context-aware reasoning, while fostering a culture of innovation and collaboration

Job Summary

  • This role will develop architectures that unify multimodal sensor data—including audio, motion, photonic, and physiological signals—into a coherent foundation for context-aware reasoning across time.
  • You will extend foundation-scale modeling into domains such as health, industrial systems, and robotics—enabling anomaly detection, forecasting, and cross-sensor understanding that bridge physics and AI.
  • At Lorenz Labs, you will work at the frontier of AI, sensors, and the physical world, helping to define a new paradigm—models that understand time, context, and matter—driving the next wave of physical intelligence.

Matching Summary

Match Score: 85

Analog Devices is seeking a Principal Engineer for their Lorenz Labs division, focusing on Time-Series and Sensor Reasoning Models. The role involves developing advanced AI models that integrate multimodal sensor data for context-aware reasoning, while fostering a culture of innovation and collaboration.

Salary

$170,775 to $256,163; Discretionary performance-based bonus; Medical, vision, dental, 401k, paid time off

Skills & Requirements

Must-have

  • Time-series foundation models
  • Multi-sensor data integration
  • Compact model architectures
  • Sensor fusion learning
  • Audio reasoning models
  • Python, PyTorch, cloud training

Nice-to-have

  • Physical intelligence systems
  • Design-time reasoning
  • Human-like intuition
  • Edge AI inference

Key Requirements

  • Ph.D. in Electrical Engineering, Computer Science, or Applied Physics
  • 10+ years of combined research and industrial experience
  • Demonstrated leadership in bridging sensing hardware
  • Record of innovation through patents, publications, or open-source contributions

Work Rights

Not specified

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