Grid Intelligence Architect — Edge-to-Cloud ML Lead

Analog Devices

Cork

On-site

EUR 120,000 - 170,000

Full time

14 days+
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Job summary

Analog Devices is seeking a highly experienced algorithm engineer and leader to shape next‑generation grid intelligence solutions. This hands‑on technical leadership role requires deep power systems knowledge, strong signal processing and ML skills, and experience across the full algorithm deployment lifecycle.

The role emphasizes collaboration with hardware, firmware, data and applications teams, with opportunities to grow into broader leadership roles. Travel is expected.

Qualifications

  • PhD in Electrical Engineering, Computer Science, Power Systems, Mathematics, Physics or related field.
  • Minimum 6 years post‑PhD experience developing and deploying practical algorithms in production systems.
  • Strong leadership with a track record of technical influence and management responsibilities.
  • Excellent communication to influence across technical and non‑technical stakeholders.

Responsibilities

  • Own and drive design and development of advanced algorithms for power system monitoring and grid analytics.
  • Develop signal processing and ML techniques to extract actionable insights from real-world sensor data.
  • Architect and deploy solutions across Edge-to-Cloud stack on constrained/embedded platforms.
  • Lead end-to-end development from modelling to validation and production deployment.
  • Mentor engineers and contribute to building a high-performance team.

Skills

Power Systems
Signal Processing
Machine Learning
Edge/Cloud
Python
MATLAB/Simulink
Embedded systems

Education

PhD in Electrical Engineering or related field

Tools

Python
MATLAB/Simulink
Embedded environments

Job description

Analog Devices is seeking a highly experienced algorithm engineer and leader to shape next‑generation grid intelligence solutions. This hands‑on technical leadership role requires deep power systems knowledge, strong signal processing and ML skills, and experience across the full algorithm deployment lifecycle.

The role emphasizes collaboration with hardware, firmware, data and applications teams, with opportunities to grow into broader leadership roles. Travel is expected.

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