senior AI Engineer

Company:

Did you know KONE moves two billion people every day? As a global leader in the elevator and escalator industry, we employ over 60,000 driven professionals in more than 60 countries worldwide joined together by a shared purpose, to shape the future of cities.

Why this role?

Design, develop, and industrialize AI/ML solutions within the R&D organization for elevator products, hardware platforms, and software-based service solutions, enabling smarter, safer, and more efficient vertical transportation across the complete product lifecycle.

What will you be doing?

• Design, build, and validate AI/ML models for predictive maintenance, fault prediction, and anomaly detection using data from elevator controllers, sensors, drives, and service systems (logs, work orders, CRM) as part of R&D programs.
• Collaborate with Product R&D to define and implement AI features in new elevator products (smart controllers, connected cars, group control algorithms, building integration features) and ensure reuse across global product platforms.
• Work with Hardware R&D teams to understand controller architecture, drives, sensors, PLCs, communication protocols, and hardware constraints, and translate this into robust AI models and edge-deployable algorithms.
• Partner with Software Service R&D to integrate AI into remote monitoring centers, diagnostic tools, mobile apps for technicians, and customer portals, ensuring solutions are designed for large installed base and scalable service operations.
• Own the AI lifecycle within R&D: data strategy, data engineering, model development, experimentation, benchmarking, validation with domain experts, and technology transfer to productization and service deployment teams.
• Implement and maintain reusable data and model pipelines (MLOps) that support cloud, on‑prem, and edge/embedded deployments, in alignment with R&D architecture and platform guidelines.
• Conduct POCs and pilots on emerging AI technologies (LLMs, computer vision, agentic systems, graph models) for use cases such as automated log analysis, code and signal interpretation, knowledge retrieval from manuals, and technician copilots.
• Ensure all AI designs comply with elevator safety, cybersecurity, and regulatory constraints, work closely with R&D safety, quality, and certification teams during design and validation phases.
• Produce high‑quality technical documentation, design specs, experiment reports, and APIs, enabling other R&D teams (product, hardware, software) to consume and extend AI components.
  
  

• Strong programming skills in Python and core ML/AI libraries (e.g., TensorFlow or PyTorch, scikit‑learn, XGBoost, Pandas, NumPy).
• Solid understanding of supervised/unsupervised learning, time‑series modeling, anomaly detection, and optimization; familiarity with model evaluation for reliability and safety‑critical systems.
• Experience working with heterogeneous data from hardware/embedded systems (sensors, controllers, PLCs, field buses) and service/software platforms (cloud, databases, APIs, ticketing/CRM).
• Familiarity with MLOps practices and tools (model versioning, CI/CD, monitoring, experiment tracking, model retraining) in an engineering/R&D context.
• Ability to work effectively with Product, Hardware, and Software R&D teams, translating technical and business requirements into AI architecture and concrete deliverables.
  
  

• Bachelor’s or Master’s degree in Computer Science, IT, Electronics, Electrical, Data Science, or any AI/ML related engineering discipline.
• 5-7 years of experience in system simulation/modelling in industrial, transportation, machinery, or similar domains.
• Strong analytical and problem‑solving skills, excellent communication, and comfort working in global, cross‑functional R&D environments.
• Strong analytical mindset, attention to detail, and structured documentation habits. Ability to create clear visualizations, dashboards, or reports to communicate simulation insights.
  
  

• Development and growth opportunities within a global organization.
• Warm and friendly working environment
• Being part of an industry leader in sustainability.