<p><p><b>About the Role : </b></p><p><p><b><br/></b></p> We are looking for an experienced Machine Learning Engineer to design, build, and deploy ML models that power business-critical solutions.
You will collaborate with cross-functional teams to deliver scalable ML systems, driving innovation and measurable business Responsibilities : </b></p><p><b><br/></b></p> - Design, develop, and deploy ML models (regression, classification, clustering, deep learning).<br/><br/></p><p> - Build and optimize data pipelines, feature engineering, and training workflows.<br/><br/></p><p> - Deploy models to production using Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).<br/><br/></p><p> - Monitor model performance, retrain, and maintain production-ready systems.<br/><br/></p><p> - Develop APIs and integrate ML solutions with enterprise applications.<br/><br/></p><p> - Stay updated on ML/AI trends and contribute innovative solutions.<br/><br/></p><p> - Collaborate with data scientists, engineers, and product managers to align with business : </b></p><p><b><br/></b></p> - 3+ years of experience in ML engineering or related field.<br/><br/></p><p> - Strong proficiency in Python; knowledge of Java/Scala/R is a plus.<br/><br/></p><p> - Expertise with ML libraries/frameworks : scikit-learn, TensorFlow, PyTorch, Keras.<br/><br/></p><p> - Hands-on with data tools : Pandas, NumPy, Spark.<br/><br/></p><p> - Experience with ML deployment (SageMaker, Azure ML, GCP AI, TensorFlow Serving, TorchServe).<br/><br/></p><p> - Familiarity with databases (SQL, MongoDB, Cassandra) and version control (Git).<br/><br/></p><p> - Understanding of DevOps/MLOps practices.<br/><br/></p><p> - Excellent problem-solving, communication, and collaboration skills.</p><br/></p> (ref:hirist.tech)