AI/ML Engineer – Industry Data Processing (OPS & Sensor Data Extraction)

Responsibilities

• Develop and deploy AI/ML models for industrial applications, including predictive maintenance, anomaly detection, and process optimization.
• Design and implement data pipelines to process large-scale sensor and operational data from industrial systems.
• Work with streaming data platforms (Kafka, Apache Flink, Spark Streaming, etc.) to manage real-time sensor data processing.
• Optimize data ingestion, storage, and transformation workflows for industrial environments.
• Collaborate with domain experts to define use cases and apply machine learning models to improve operational efficiency.
• Implement feature engineering and statistical techniques to extract meaningful insights from raw industry data.
• Ensure model interpretability and scalability for real-world industrial applications.
• Work with IoT devices, edge computing, and cloud platforms (AWS, Azure, GCP) for seamless AI/ML deployment.
• Perform A/B testing and validation of AI-driven recommendations.
• Ensure compliance with data security and governance policies.

Qualifications

Education

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related field.

Required Experience

• 3+ years of experience in AI/ML development with a focus on industry operations and sensor data.
• Proficiency in Python, R, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-Learn, etc.).
• Experience with Big Data technologies (Hadoop, Spark, Databricks, etc.).
• Strong understanding of time-series data, anomaly detection, and predictive analytics.
• Hands-on experience with ETL pipelines, data lakes, and cloud-based AI services.
• Familiarity with industrial automation, PLCs, SCADA systems, and IoT platforms.
• Strong problem-solving skills and ability to work in a cross-functional team environment.

Good to Have

• Experience in reinforcement learning, deep learning, or computer vision for industrial applications.
• Knowledge of manufacturing processes, energy systems, or industrial IoT (IIoT).
• Certification in AWS/GCP/Azure Machine Learning services.
• Understanding of edge AI and embedded AI model deployment.