AI, ML

Position : AI/ML & Robotics Automation Engineer Industrial Automation Location: Bangalore (On-Site) Experience Level: years in Industrial IoT Employment Type: Full-timeAbout CitriotCitriot is a pioneering deep tech company specializing in Industrial Internet of Things (IIoT), Computer Vision, AI/ML, and Industrial Automation. We develop cutting-edge solutions for predictive maintenance, equipment monitoring, and anomaly detection across automotive, oil & gas, pharmaceuticals, chemicals, metals, and manufacturing industries.Citriot is revolutionizing industrial operations through deep tech convergence of IIoT, AI/ML, Computer Vision, and Industrial Automation. Our solutions enable predictive maintenance and intelligent automation across diverse manufacturing sectors.Position Overview We are seeking a talented AI/ML Engineer and Robotics Automation Engineer to design, develop, and deploy machine learning models and robotic automation systems for industrial automation applications. You will work on challenging problems involving predictive analytics, computer vision, intelligent automation systems, autonomous robotics, and collaborative industrial solutions.Key ResponsibilitiesAI/ML Responsibilities: Design and develop AI/ML models for predictive maintenance, anomaly detection, and equipment monitoring Implement computer vision solutions for quality inspection, defect detection, and visual surveillance Build and optimize deep learning models (CNN, RNN, LSTM, Transformers) for industrial applications Develop time-series analysis and forecasting models for sensor data from IIoT devices Deploy ML models on edge devices and cloud infrastructure with scalability considerations Integrate AI/ML solutions with existing IIoT platforms and industrial automation systems Collaborate with robotics and automation teams to implement intelligent control systems Perform data preprocessing, feature engineering, and model validation on industrial datasets Monitor model performance in production and implement continuous improvement strategies Document technical specifications, model architectures, and deployment proceduresRobotics Responsibilities: Design and develop robotic automation systems for industrial applications Implement robot control algorithms and motion planning systems Integrate computer vision and AI/ML models with robotic systems for intelligent decision-making Develop autonomous navigation and obstacle avoidance solutions Program and configure industrial robots (6-axis arms, collaborative robots, AGVs/AMRs) Design and implement robotic end-effectors and custom gripper mechanisms Integrate sensors (LiDAR, cameras, force/torque sensors) with robotic systems Develop simulation environments for robot testing and validation Implement safety protocols and fail-safe mechanisms for human-robot collaboration Collaborate with AI/ML teams to deploy perception and decision-making models on robots Optimize robot trajectories and cycle times for manufacturing efficiency Provide technical support for deployed robotic systems and troubleshoot issuesRequired Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Electrical Engineering, Robotics, Mechatronics, or related field 2-5 years of hands-on experience in AI/ML development or robotics/automation engineering (freshers with exceptional skills may be considered) Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn, Keras) Experience with computer vision libraries (OpenCV, PIL, YOLO, ResNet) Strong knowledge of robotics fundamentals: kinematics, dynamics, control theory Experience with robot programming (ROS/ROS2, Python, C++) Proficiency in motion planning and path optimization algorithms Solid understanding of machine learning algorithms, deep learning architectures, and statistical methods Experience with industrial robots (ABB, KUKA, Fanuc, Universal Robots) or mobile robots Knowledge of computer vision integration for robotic perception Experience with data preprocessing, feature engineering, and model optimization techniques Knowledge of MLOps practices and tools (MLflow, Kubeflow, Docker, Kubernetes) Familiarity with cloud platforms (AWS, Azure, GCP) and edge computing Understanding of control systems (PID, MPC, adaptive control) Experience with simulation tools (Gazebo, CoppeliaSim, MATLAB/Simulink) Strong programming skills and understanding of data structures and algorithmsPreferred Qualifications Experience in industrial automation, manufacturing, or process industries Knowledge of IIoT protocols (MQTT, OPC-UA, Modbus) and sensor integration Experience with edge AI deployment on devices like NVIDIA Jetson, Raspberry Pi, or industrial controllers Familiarity with time-series databases (InfluxDB, TimescaleDB) and real-time analytics Experience with reinforcement learning for control systems Understanding of industrial processes and maintenance practices Publications or contributions to AI/ML open-source projects Knowledge of explainable AI (XAI) and model interpretability techniques Experience with collaborative robots (cobots) and human-robot interaction Knowledge of AI/ML integration with robotic systems Experience with SLAM, sensor fusion, and autonomous navigation Familiarity with industrial automation protocols (PLC, SCADA, OPC-UA) Experience in manufacturing environments (automotive, electronics, logistics) Knowledge of mechanical design and CAD tools (SolidWorks, AutoCAD) Experience with embedded systems and real-time operating systems Familiarity with IIoT integration and Industry 4.0 concepts Certification in industrial robot programming or safetyTechnical SkillsAI/ML Technical Skills: Languages: Python, C++, Java, SQL ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost Computer Vision: OpenCV, YOLO, Mask R-CNN, ResNet, EfficientNet Tools: Jupyter, Git, Docker, Kubernetes, Apache Spark Databases: PostgreSQL, MongoDB, InfluxDB, Redis Cloud: AWS SageMaker, Azure ML, Google Cloud AI PlatformRobotics Technical Skills: Robotics: ROS/ROS2, MoveIt, Navigation Stack, TF, URDF Programming: Python, C++, MATLAB, LabVIEW Simulation: Gazebo, CoppeliaSim, V-REP, MATLAB/Simulink Computer Vision: OpenCV, PCL (Point Cloud Library) Control Systems: PID tuning, state-space control, trajectory planning Hardware: LiDAR, depth cameras, IMU, encoders, actuators Tools: Git, Docker, Linux, CMake Protocols: Modbus, Ethernet/IP, OPC-UA, MQTTJoin our team to drive innovation and transform the manufacturing and facility management landscape with IoT and AI