Senior Machine Learning Engineer

As a Senior Machine Learning Engineer at a fast-growing global AI product company specializing in industrial operations transformation through Machine Learning, Predictive Analytics, and Agentic AI, you will have the opportunity to work on large-scale industrial datasets. Your role will involve building production-grade ML systems and developing next-generation AI solutions with real-world business impact. Key Responsibilities: - Own the end-to-end Machine Learning lifecycle from problem definition to production deployment - Build forecasting, anomaly detection, and predictive models using time-series data - Design and develop Agentic AI applications leveraging LLMs, embeddings, and orchestration frameworks - Develop scalable ML pipelines, monitoring, and model evaluation systems - Collaborate with Product, Engineering, and Data teams to deliver AI-powered solutions Qualifications Required: - 46 years of experience in Machine Learning / Applied AI - Strong experience in Time-Series Modeling, Forecasting, and Anomaly Detection - Hands-on experience deploying and monitoring ML models in production environments - Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and Scikit-learn - Experience with LLMs, Agentic AI systems, LangChain, LangGraph, DSPy, or similar frameworks - Understanding of MLOps, model monitoring, and drift detection Good to Have: - Industrial AI, IoT, Sensor Data, or Predictive Maintenance experience - Exposure to Databricks, Snowflake, BigQuery, Spark, or distributed data systems If you are interested or know someone who could be a great fit for this role, please share your profile at the provided email address. (Note: Additional details about the company were not included in the job description.) As a Senior Machine Learning Engineer at a fast-growing global AI product company specializing in industrial operations transformation through Machine Learning, Predictive Analytics, and Agentic AI, you will have the opportunity to work on large-scale industrial datasets. Your role will involve building production-grade ML systems and developing next-generation AI solutions with real-world business impact. Key Responsibilities: - Own the end-to-end Machine Learning lifecycle from problem definition to production deployment - Build forecasting, anomaly detection, and predictive models using time-series data - Design and develop Agentic AI applications leveraging LLMs, embeddings, and orchestration frameworks - Develop scalable ML pipelines, monitoring, and model evaluation systems - Collaborate with Product, Engineering, and Data teams to deliver AI-powered solutions Qualifications Required: - 46 years of experience in Machine Learning / Applied AI - Strong experience in Time-Series Modeling, Forecasting, and Anomaly Detection - Hands-on experience deploying and monitoring ML models in production environments - Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and Scikit-learn - Experience with LLMs, Agentic AI systems, LangChain, LangGraph, DSPy, or similar frameworks - Understanding of MLOps, model monitoring, and drift detection Good to Have: - Industrial AI, IoT, Sensor Data, or Predictive Maintenance experience - Exposure to Databricks, Snowflake, BigQuery, Spark, or distributed data systems If you are interested or know someone who could be a great fit for this role, please share your profile at the provided email address. (Note: Additional details about the company were not included in the job description.)