Machine Learning Engineer (Python or R)

Job SummaryWe are looking for a Machine Learning Engineer with 3+ years of experience in building, training, and deploying machine learning models. The ideal candidate will have strong programming skills in Python or R and hands-on experience working with data, model development, evaluation, and production deployment. You will collaborate with data scientists, software engineers, and business stakeholders to design scalable ML solutions that solve real-world problems.Key Responsibilities● Develop, train, and deploy machine learning models using Python or R.● Work with structured and unstructured data to build predictive and analytical solutions.● Perform data preprocessing, feature engineering, model selection, and hyperparameter tuning.● Evaluate model performance using appropriate metrics and validation techniques.● Build and maintain ML pipelines for training, testing, and inference.● Collaborate with data engineers and software teams to integrate models into applications and workflows.● Develop APIs or services to expose machine learning models for production use.● Monitor model performance in production and retrain models as needed.● Analyze business requirements and translate them into machine learning solutions.● Document model design, experiments, and deployment processes.● Troubleshoot, optimize, and maintain ML systems in production environments.Required Qualifications● Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.● 3+ years of experience in Machine Learning, Data Science, or Software Development.● Strong programming skills in Python or R.● Hands-on experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, caret, tidymodels, or similar tools.● Solid understanding of supervised and unsupervised learning techniques.● Experience with data preprocessing, feature engineering, and model evaluation.● Knowledge of SQL and working with relational or non-relational databases.● Experience building and deploying ML models in production environments.● Familiarity with Git, Docker, and CI/CD workflows.● Strong analytical, problem-solving, and communication skills.Preferred Qualifications● Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.● Familiarity with MLOps tools such as MLflow, Kubeflow, Airflow, or SageMaker.● Experience with model monitoring, drift detection, and retraining strategies.● Knowledge of NLP, computer vision, time series forecasting, or recommendation systems.● Experience working in Agile or cross-functional product teams.● Exposure to big data tools such as Spark or Databricks.