Help us give machines the ability to sense when things go wrong and adapt in real time.

At IntuiCell, we’re building the digital nervous system for intelligent agents. Deeply inspired by how real biological systems learn, adapt, and interact. We’re not refining known architectures - we’re developing new ones, from first principles.

We’re looking for an Applied Research Engineer with a background in anomaly detection or predictive maintenance. You’ll work closely with our research team to design and test learning systems that interact with real-world dynamics. This is a role for someone who’s used to working across models, sensors, and systems. Someone who enjoys the friction that comes from putting ideas into motion.

What You'll Do

• Implement and test learning algorithms for anomaly detection, predictive maintenance, and adaptive control, both in simulated and physical automation environments.

• Design experiments that validate hypotheses about system reliability, failure modes, and adaptive responses.

• Work across disciplines - sensor integration, control, learning dynamics
  

• Build and maintain codebases and tooling for iterative development
  

• Contribute to a research culture that values clarity, experimentation, and building things that work

What You Bring

• 2–6 years of experience in anomaly detection, fault detection or predictive maintenance within automation or control systems.
  

• Strong systems thinking and engineering instincts
  

• Proficient in at least one low-level language (e.g., C++, Rust)
  

• Experience working with automation systems, control loops, sensor networks, or industrial equipment.
  

• Comfortable reading papers and translating them into real-time experiments

Bonus Signals

• Experience from industrial automation, control systems, or reliability engineering.

• Exposure to time-series analysis, predictive modeling, or condition monitoring.

• Exposure to neuro-inspired control, adaptive systems, or sensor fusion
  

• Publications or demonstrators that reflect full-stack ownership of experiments
  
  

Why IntuiCell

We’re a research-heavy team building the kind of intelligent systems that can learn from the world and not just from data. Our platform is built from scratch, our models are derived from biology, and our goal is to bring about intelligence that is real-time, robust, and embodied, including systems that can monitor their own health and adapt when things go wrong.

You’ll work in person with a team of researchers, engineers, and scientists in Malmö/Lund, because this kind of work moves faster when we think together, in the same room.

Sound like your kind of challenge?

Reach out, apply, or start a conversation. We’re looking for curious, capable people with a systems mindset and a builder’s instinct.