Job Summary:
We are seeking an innovative and skilled AI Developer to design, develop, and implement artificial intelligence and machine learning solutions for our digital platforms. The ideal candidate will have a strong background in programming, data science, and AI model deployment, with the ability to turn complex problems into practical, intelligent systems.
Key Responsibilities:
- Design, develop, and deploy AI and machine learning models to solve business problems.
- Integrate AI features such as chatbots, recommendation systems, and predictive analytics into applications or websites.
- Work with data engineers to preprocess and clean large datasets for training and evaluation.
- Develop and manage APIs for AI-driven functionalities.
- Collaborate with software developers, data scientists, and product teams to integrate AI solutions seamlessly.
- Continuously monitor, test, and improve model performance.
- Research and implement the latest AI tools, libraries, and frameworks.
- Maintain clear documentation for model design, training, and deployment processes.
Required Skills and Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
- Proven experience as an AI Developer, Machine Learning Engineer, or Data Scientist.
- Strong programming skills in Python (TensorFlow, PyTorch, scikit-learn, OpenAI API, etc.).
- Understanding of NLP (Natural Language Processing), Computer Vision, or Predictive Modeling.
- Experience with AI APIs (e.g., OpenAI, Google Cloud AI, Hugging Face, etc.).
- Proficiency with data preprocessing, model training, and evaluation techniques.
- Familiarity with RESTful APIs, webhooks, and integration with front-end systems.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud AI Services.
- Excellent analytical and problem-solving skills.
Preferred Qualifications (Optional):
- Experience with AI chatbot development and Google Sheet / API integrations.
- Knowledge of LangChain, Vector Databases (Pinecone, Chroma), or RAG (Retrieval-Augmented Generation) architecture.
- Familiarity with MLOps tools for continuous model training and deployment.
- Understanding of ethical AI and data privacy considerations.