[Internal] Machine Learning/AI Engineer Trainee

Job Description

About the position

The Machine Learning/AI Engineer Trainee position is a full-time, unpaid program designed for aspiring software engineers and AI enthusiasts. This 3-month program offers hands-on experience in building and implementing AI solutions, focusing on Natural Language Processing (NLP) and software deployment. Trainees will work under the mentorship of experienced professionals, enhancing their skills in designing scalable systems, deploying machine learning models, and building APIs, with the potential for a paid internship upon exceptional performance.

Responsibilities
• Participate in hands-on projects to build and implement AI solutions.
• Design and implement NLP models for tasks such as text classification and sentiment analysis.
• Integrate Retrieval-Augmented Generation (RAG) frameworks with vector-based solutions.
• Build and maintain scalable APIs using FastAPI for real-world deployment of AI models.
• Develop expertise in containerization tools like Docker for deployment and scalability.
• Implement CI/CD pipelines for automated testing, integration, and deployment of AI solutions.
• Work on data preprocessing, feature extraction, and building robust data pipelines.
• Integrate ML models into end-to-end production systems, focusing on scalability and performance.
• Collaborate with a remote team and enhance documentation skills.

Requirements
• Bachelor’s or Master’s degree in Computer Science, Data Science, or related fields.
• Interest and hands-on experience with NLP, RAG, and machine learning frameworks.
• Proficiency in Python and API development using frameworks like FastAPI.
• Strong problem-solving skills and a detail-oriented approach to software development.

Nice-to-haves
• Experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Familiarity with containerization tools like Docker.
• Knowledge of CI/CD practices and tools.

Benefits
• Hands-on experience with real-world projects.
• Mentorship from experienced professionals.
• Potential for a paid internship opportunity after the program.