Design, develop, and implement AI agents for various applications.
Train and fine-tune machine learning models using structured and unstructured datasets.
Work with deep learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
Implement reinforcement learning techniques to enhance AI agent performance.
Perform data preprocessing, augmentation, and feature engineering.
Optimize model performance through hyperparameter tuning and algorithm optimization.
Integrate AI solutions into real-world applications and assist in deployment.
Collaborate with data scientists, software engineers, and business teams to understand requirements and deliver AI-driven solutions.
Conduct research and stay updated with the latest trends and advancements in AI and ML.
Document research findings, methodologies, and results effectively.
Requirements:
Strong programming skills in Python (knowledge of C++/Java is a plus).
Experience with machine learning frameworks like TensorFlow, PyTorch, or Keras.
Understanding of deep learning, natural language processing (NLP), and computer vision techniques.
Familiarity with reinforcement learning concepts and their applications.
Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
Experience working with large datasets and cloud computing platforms (AWS, Google Cloud, or Azure) is a plus.
Strong problem-solving skills and the ability to work in a collaborative team environment.
Excellent communication and documentation skills.