Design, develop, and deploy machine learning models for various use cases (classification, regression, NLP, CV, etc.)
Preprocess, clean, and transform large datasets for training and testing
Conduct model evaluation, performance tuning, and error analysis
Collaborate with data engineers, product managers, and business stakeholders to deliver intelligent solutions
Implement and manage scalable ML pipelines using tools like MLflow, Airflow, or Kubeflow
Work with cloud platforms such as AWS, Azure, or GCP for model training and deployment
Stay updated with the latest advancements in AI/ML technologies and frameworks
Strong programming skills in Python and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch
Experience with model deployment and MLOps practices
Good understanding of data structures, algorithms, and statistics
Hands-on experience with cloud platforms (AWS/GCP/Azure)
Proficiency in SQL and working with databases/data warehouses
Knowledge of Docker/Kubernetes is a plus
Excellent problem-solving and communication skills
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data EngineerEmployement Type: Full time