Machine Learning Engineer with AI Project Experience:

Responsibilities:

• Design, build, and deploy ML models for real-time and batch processing use cases.

• Work on end-to-end AI projects: from data exploration and feature engineering to model deployment and monitoring.

• Collaborate with software engineers, data scientists, and product teams to define AI requirements and deliver integrated solutions.

• Optimize model performance and ensure reliability and scalability in production environments.

• Conduct model validation, A/B testing, and continuous performance monitoring.

• Develop and maintain data pipelines, model training scripts, and reusable ML components.

• Stay current with the latest ML research, tools, and best practices.

Required Skills & Qualifications:

• Bachelor's or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field.

• 2+ years of experience in machine learning or AI model development.

• Proficient in Python and libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, or Keras.

• Strong understanding of supervised, unsupervised, and deep learning techniques.

• Experience in feature engineering, model evaluation metrics, and overfitting/underfitting prevention.

• Familiar with end-to-end ML lifecycle, including data preprocessing, model training, evaluation, deployment, and monitoring.

• Experience with cloud platforms such as AWS (SageMaker), Azure ML, or GCP AI Platform.

• Good grasp of APIs, containers (Docker), version control (Git), and CI/CD pipelines for ML workflows.

Preferred Qualifications:

• Experience with LLMs, NLP, Computer Vision, or Recommendation Systems.

• Familiarity with MLOps tools (MLflow, Kubeflow, Airflow).

• Knowledge of data annotation tools and working with unstructured data (text, images, video).

• Contributions to open-source ML projects or research papers.