Role Overview
We are looking for a skilled and motivated AI Developer to join our growing data and AI team. This role is ideal for a developer with a solid foundation in AI and machine learning concepts. You will work closely with the Lead AI Developer to design, implement, and optimize AI models and applications, contributing to the development of innovative solutions that solve real-world business problems.
Key Responsibilities
Model Development: Assist in the development, training, and testing of machine learning and deep learning models.
Data Handling: Participate in data collection, cleaning, preprocessing, and analysis to prepare high-quality datasets for model training.
Collaboration: Work with the lead developer and other team members to understand project requirements, contribute to solution design, and integrate AI components into existing systems.
Code Implementation: Write clean, efficient, and well-documented code in Python, adhering to established coding standards and best practices.
System Optimization: Support the team in fine-tuning and optimizing models for performance and scalability.
Documentation: Create and maintain technical documentation for models, code, and processes.
Key Requirements
Educational Background:
Bachelor's or Master's degree in Computer Science, IT, or a related technical field.
Work Experience: 1 to 4 years of professional experience in an AI/ML or software development role.
Technical Skills:
Proficiency in Python and familiarity with key libraries like Pandas, NumPy, and Scikit-learn.
Experience with at least one major deep learning framework (TensorFlow or PyTorch).
Basic knowledge of machine learning algorithms, statistical concepts, and data visualization techniques.
Familiarity with version control systems, especially Git.
Understanding of data handling and processing pipelines.
Soft Skills:
Strong problem-solving and analytical skills.
Eager to learn new technologies and apply them effectively.
Good communication and teamwork skills.
Nice to Have
Experience with MLOps, vector databases, and RAG frameworks.
Knowledge of multi-modal AI, AutoML, or reinforcement learning.
Certifications in cloud AI/ML (AWS, Azure, GCP).
Contributions to open-source projects, research, or patents.
Domain expertise in industries like FinTech, Healthcare, or Retail.