Lead AI Engr

Honeywell Honeywell · Industrial · Bengaluru, Karnataka, India

Lead AI Engineer role focused on designing, developing, and deploying AI/ML solutions for smart buildings and industrial automation. Responsibilities include architecting models for predictive maintenance, energy optimization, and anomaly detection, integrating AI into control systems, leading data engineering pipelines, exploring emerging AI technologies, applying reinforcement learning, and managing a team. Requires strong Python, ML framework, IoT, and control systems knowledge, with experience in cloud and edge computing.

What you'd actually do

  1. Architect and implement AI/ML models for predictive maintenance, energy optimization, process automation, and anomaly detection in building and industrial systems.
  2. Integrate AI solutions into Building Management Systems (BMS) and Industrial Control Systems (ICS), including SCADA and PLC environments.
  3. Design pipelines for collecting, cleaning, and processing large-scale building and industrial data (temperature, occupancy, energy usage, machine performance).
  4. Drive innovation by exploring emerging technologies such as generative AI, digital twins, and autonomous control systems.
  5. Apply reinforcement learning or adaptive control for dynamic building and industrial environments.

Skills

Required

  • Python
  • TensorFlow/PyTorch
  • data science libraries
  • IoT and industrial protocols (BACnet, Modbus, MQTT, OPC-UA)
  • control systems
  • HVAC
  • energy optimization
  • industrial automation principles
  • supervised/unsupervised learning
  • time-series forecasting
  • reinforcement learning
  • anomaly detection
  • predictive maintenance algorithms
  • SCADA systems
  • PLC programming basics
  • industrial process optimization
  • Industry 4.0 concepts
  • smart factory technologies
  • AWS, Azure, or Google Cloud
  • edge devices
  • real-time inference
  • lead technical teams
  • manage complex projects

Nice to have

  • PhD preferred
  • 8+ years in AI/ML development
  • 3 years in building or industrial automation
  • smart building platforms
  • energy management solutions
  • generative AI
  • digital twins
  • autonomous control systems

What the JD emphasized

  • lead a team
  • AI/ML models
  • predictive maintenance
  • energy optimization
  • process automation
  • anomaly detection
  • real-time decision-making
  • sensor, IoT, and industrial control data
  • Building Management Systems (BMS)
  • Industrial Control Systems (ICS)
  • SCADA
  • PLC
  • IoT devices
  • industrial protocols
  • edge computing frameworks
  • large-scale building and industrial data
  • scalable data storage
  • generative AI
  • digital twins
  • autonomous control systems
  • reinforcement learning
  • adaptive control
  • dynamic building and industrial environments
  • accuracy, efficiency, and reliability
  • lead a team of AI engineers and data scientists
  • define AI strategy
  • cybersecurity standards
  • industrial safety protocols
  • energy regulations
  • industry standards
  • Python
  • TensorFlow/PyTorch
  • data science libraries
  • IoT
  • industrial protocols (BACnet, Modbus, MQTT, OPC-UA)
  • control systems
  • HVAC
  • energy optimization
  • industrial automation principles
  • supervised/unsupervised learning
  • time-series forecasting
  • reinforcement learning
  • anomaly detection
  • predictive maintenance algorithms
  • SCADA systems
  • PLC programming basics
  • industrial process optimization
  • Industry 4.0 concepts
  • smart factory technologies
  • emerging trends
  • practical solutions
  • rapid prototyping
  • proof-of-concept development
  • technology scouting
  • problem-solving mindset
  • creative and disruptive solutions
  • AWS, Azure, or Google Cloud
  • edge devices
  • real-time inference
  • lead technical teams
  • manage complex projects
  • 8+ years in AI/ML development
  • 3 years in building or industrial automation
  • smart building platforms
  • SCADA systems
  • energy management solutions
  • delivering innovative AI solutions
  • automation domains

Other signals

  • design, develop, and deploy AI-driven solutions
  • optimize HVAC, lighting, security, energy management, and industrial processes
  • lead a team to deliver scalable AI solutions
  • AI Solution Design & Development
  • System Integration
  • Data Engineering
  • Innovation & Research
  • Performance Optimization
  • Leadership & Collaboration
  • Compliance & Security
  • Python, TensorFlow/PyTorch
  • reinforcement learning
  • anomaly detection
  • predictive maintenance
  • SCADA systems
  • edge computing
  • AWS, Azure, or Google Cloud