Machine Learning Engineer

Responsibilities

• Develop and optimize machine learning models for predictive analytics, NLP, computer vision, and recommendation systems.
• Work with large datasets, perform feature engineering, and ensure data quality for model training.
• Deploy and maintain machine learning models in production environments using MLOps best practices.
• Collaborate with data engineers and software developers to integrate models into applications.
• Optimize model performance using techniques like hyperparameter tuning, transfer learning, and distributed training.
• Stay updated with the latest advancements in AI and machine learning technologies.
• Implement real-time and batch processing pipelines for AI-driven applications.
• Conduct A/B testing and performance evaluations of machine learning models.

Requirements

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Minimum 3-4 years of experience in machine learning and AI development.
• Strong programming skills in Python, TensorFlow, PyTorch, and Scikit-learn.
• Experience with cloud-based ML services (AWS SageMaker, Azure ML, or Google Vertex AI).
• Proficiency in data preprocessing, feature selection, and model evaluation.
• Hands-on experience with big data frameworks (Spark, Hadoop) and databases (SQL, NoSQL).
• Familiarity with MLOps, model deployment, and API development.
• Strong problem-solving skills and ability to work with cross-functional teams.