Senior Machine Learning Engineer

About us:

Indurex is an AI-native engineering-first company focused on keeping complex cyber-physical systems resilient safe and secure. Our platform unifies safety process and cybersecurity data to deliver context-aware AI-scored incidents and actionable recommendations - complementing existing SCADA/DCS historians and security tools. With headquarters in Amsterdam Indurex partners with regional and global energy manufacturing utilities data center and pipeline operators to safeguard the systems that power and connect our world.

In this role you will work on advanced AI initiatives at the intersection of cybersecurity and industrial systems. You will influence how our ML models bolster industrial threat detection safeguard critical infrastructure and anticipate operational disruptions. You will join a global tech team of engineers security researchers and technologists with deep backgrounds in OT automation large-scale AI systems and mission-critical operations.

Your responsibilities will include:

• Design ML models for anomaly detection threat prediction and pattern recognition in cyber-physical environments.

• Work with large-scale network data sensor logs time-series and event correlation models.

• Develop explainable AI systems suitable for regulated industries.

• Collaborate with full-stack and security engineers to embed intelligence into the platform.

• Build and optimize ML pipelines using modern tools like TensorFlow PyTorch and/or Scikit-learn.

• Ensure robust model validation and compliance with cyber security standards.

• Stay informed on the latest advancements in AI machine learning and cyber security to ensure our technology remains at the forefront.

• Masters degree in Artificial Intelligence Computer Science Mathematics Data Science or related

• Minimum of 5 years of experience in AI Machine learning and/or Data Science preferably in Applied ML cybersecurity or Industrial domains.

• Solid foundation in supervised and unsupervised learning time-series forecasting anomaly detection.

• Proficient in Python ML frameworks and cloud ML services (AWS/GCP/Azure).

• Understanding of data engineering data privacy and pipeline architecture.

• Ability to translate raw data into meaningful interpretable insights for end users.

• A proactive problem-solving mindset with a passion for innovation and cutting-edge technology. Ability to undertake and complete tasks independently meet schedules and delivery timelines.