Description

You will lead a team of data scientists to define, develop, and deploy AI-powered models for energy efficiency and predictive maintenance.

Responsibilities

• Develop and deploy AI/ML models for predictive maintenance, anomaly detection, and energy efficiency optimization.
• Process real-time IoT sensor data, including temperature and power consumption, to extract actionable insights.
• Design and build scalable data pipelines for handling real-time streaming data.
• Collaborate with engineering teams to integrate AI solutions into cloud-based platforms.
• Build and maintain data-driven dashboards for monitoring performance and engagement.

Required Skills

• 6+ years of experience in Data Science, AI, or Machine Learning.
• 3+ years of hands-on development experience.
• Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, FastAPI).
• Experience with IoT sensor data, real-time streaming, and time-series forecasting.
• Hands-on expertise in SQL, NoSQL, and Big Data processing (Spark, Hadoop, Apache Kafka).
• Strong background in MLOps and cloud-based AI deployment (AWS, GCP, or Azure).
• Experience in data engineering, ETL, and building scalable AI infrastructure.
• Ability to work independently on complex problems and drive AI adoption.

Preferred Skills

• Knowledge of predictive maintenance frameworks.
• Experience with AutoML, reinforcement learning, or edge AI for IoT applications.

Key Skills

Education

Any Graduate