AI Engineer at Project Growth

Key Responsibilities

• Model Development: Design, develop, and optimize machine learning models for personalized learning and career guidance.
• Backend Integration: Work with backend engineers to integrate AI models into a TypeScript-based platform.
• Data Processing: Analyze and preprocess large datasets to train machine learning models effectively.
• API Development: Implement and maintain APIs that power AI-driven features such as recommendations and learning paths.
• AI Research: Stay updated with the latest advancements in NLP, computer vision, and recommendation systems.
• Model Performance & Scalability: Monitor AI model performance and continuously improve accuracy, efficiency, and scalability.
• Ethical AI Practices: Ensure fairness, bias mitigation, and model explainability for responsible AI use.

What Success Looks Like

• Advanced AI Solutions: Deliver AI-driven features that improve user experience and learning outcomes.
• Scalable Models: Deploy high-performance AI models capable of handling large-scale user interactions.
• Seamless Integration: Smooth implementation of AI solutions within the existing platform.
• Responsible AI Practices: Maintain ethical AI principles, ensuring unbiased and fair recommendations.

Qualifications
Experience

• Bachelor's or Master’s degree in Computer Science, Data Science, AI, or related fields.
• 2+ years experience integrating AI models into applications using TypeScript.

Skills

• Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Fluent English communication skills, written and verbal.
• Hands-on experience in NLP, recommendation systems, or personalization algorithms.
• Familiarity with cloud platforms (AWS, GCP, or Azure) for AI model deployment.

Preferred Skills

• Experience with MLOps tools for CI/CD, model versioning, and monitoring.
• Familiarity with TypeScript frameworks like NestJS for backend AI services.
• Knowledge of big data technologies such as Apache Spark or Hadoop.
• Background in education technology or career development systems.
• Understanding of AI ethics, fairness, and explainability frameworks.