Key Responsibilities
- Design, develop, and deploy machine learning and deep learning systems for scalable applications.
- Implement appropriate ML algorithms based on business and technical requirements.
- Conduct machine learning experiments, model training, validation, and performance tuning.
- Build self-learning systems that continuously improve using data-driven approaches.
- Apply statistical and data science principles to solve complex business problems.
- Collaborate with data engineers and software teams to integrate ML models into production systems.
Requirements
- Proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, PyTorch, OpenCV, and NumPy.
- Strong understanding of machine learning algorithms and deep learning techniques.
- Experience with optimizing models for accuracy, scalability, and performance in production environments.
- Ability to analyze large datasets to extract meaningful insights and patterns.
- Familiarity with latest advancements in AI, ML, and deep learning technologies.