AI ML Engineer

Role OverviewWe are looking for an AI/ML Engineer with 2 - 6 years of industry experience to develop and deploy machine learning solutions for industrial and smart manufacturing use cases. The role involves working with real-world industrial data, developing predictive and analytical models, and translating business and operational requirements into scalable AI/ML solutions.The ideal candidate should have strong fundamentals in machine learning, Python, data processing, model development, and deployment, along with an interest in applying AI to manufacturing, industrial automation, and operational optimization.Key ResponsibilitiesDesign, develop, train, and evaluate machine learning models for industrial and manufacturing use cases.Analyze large and complex datasets to identify patterns, trends, anomalies, and opportunities for optimization.Perform data preprocessing, feature engineering, model selection, and performance evaluation.Develop solutions for use cases such as predictive maintenance, anomaly detection, quality prediction, process optimization, forecasting, and equipment monitoring.Work with structured and time-series data generated from industrial equipment, machines, sensors, and operational systems.Develop and optimize ML pipelines for data preparation, model training, validation, and deployment.Collaborate with domain experts, data engineers, software engineers, and business stakeholders to understand requirements and translate them into technical solutions.Deploy machine learning models into production environments and monitor model performance.Troubleshoot model and data-related issues and continuously improve model accuracy, reliability, and scalability.Develop reusable code, APIs, and components to integrate ML models with enterprise and industrial applications.Document models, methodologies, experiments, results, and technical implementations.Stay updated with emerging AI/ML techniques, industrial AI trends, and smart manufacturing technologies.Required Technical SkillsStrong programming experience in Python.Good understanding of Machine Learning algorithms and concepts.Experience with libraries/frameworks such as Scikit-learn, Pandas, NumPy, and preferably TensorFlow or PyTorch.Strong understanding of data preprocessing, feature engineering, model training, validation, and evaluation.Experience working with time-series data is preferred.Good understanding of statistical concepts and data analysis.Experience with SQL and relational databases.Understanding of model deployment and productionization of ML solutions.Familiarity with Git and software development best practices.Good problem-solving and analytical skills.Preferred SkillsExperience in Industrial AI, Smart Manufacturing, Industry 4.0, or Industrial IoT (IIoT).Experience with predictive maintenance, anomaly detection, forecasting, or quality inspection.Exposure to sensor data, machine/equipment data, telemetry, or real-time industrial data.Knowledge of computer vision for manufacturing or quality inspection use cases.Exposure to cloud platforms such as AWS, Azure, or GCP.Familiarity with Docker, Kubernetes, or CI/CD for ML deployment.Knowledge of MLOps concepts and tools.Exposure to Generative AI/LLMs is an added advantage.