Requirements
Core Responsibilities:
Design, develop, and deploy machine learning models for production use.
Collaborate with cross-functional teams (Data Engineering, Product, and Software Development) to understand and solve complex business problems using AI/ML solutions.
Conduct data preprocessing, feature engineering, model selection, training, evaluation, and optimization.
Implement scalable ML pipelines using frameworks like TensorFlow, PyTorch, or Scikit-learn.
Monitor and maintain ML models post-deployment, ensuring performance and relevance.
Stay updated with the latest trends and research in artificial intelligence and machine learning, and integrate best practices into ongoing projects.
Qualification:
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
2–5 years of hands-on experience in AI/ML development.
Demonstrated experience in delivering production-grade machine learning solutions.
Required Skills:
Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn, XGBoost, etc.).
Strong understanding of data structures, algorithms, and model evaluation metrics.
Experience with NLP, computer vision, or recommendation systems is a plus.
Familiarity with data handling tools (Pandas, NumPy), databases (SQL/NoSQL), and cloud services (AWS, GCP, Azure).
Understanding of MLOps concepts and tools (e.g., MLflow, Docker, Kubernetes, CI/CD pipelines).
Excellent problem-solving, communication, and collaboration skills.
