Software Engineering Intern

Summary

Join Luminexis.AI's AI Services Consulting team for a three-month internship. You will collaborate with senior engineers to develop and deploy AI/ML solutions, support client engagements, and gain hands-on experience across the software development lifecycle. The internship involves building data pipelines, implementing machine learning models, integrating AI/ML services, and deploying projects on cloud platforms. You will also contribute to data engineering, participate in code reviews, and engage in team meetings and client presentations. The role requires proficiency in Python, familiarity with machine learning frameworks, and strong analytical and communication skills. This is an immersive opportunity to gain practical experience in AI/ML development and deployment.

Requirements

• Pursuing or recently completed B.S./M.S. in Computer Science, Data Science, Engineering, or related
• Coursework or projects in machine learning, statistics, and data analysis
• Proficiency in Python and experience with Pandas/NumPy
• Familiarity with scikit-learn, TensorFlow, or PyTorch
• Basic SQL knowledge and data-visualization experience (Matplotlib, Seaborn, Plotly)
• Understanding of Git and software development workflows
• Exposure to cloud platforms and eagerness to learn MLOps
• Strong analytical and debugging skills
• Clear written and verbal communication for technical documentation
• Ability to manage multiple tasks and learn quickly in a fast-paced environment
• Enthusiasm for AI/ML and its business applications

Responsibilities

• Build data pipelines: preprocessing, feature engineering, model training
• Implement supervised/unsupervised learning models
• Develop basic NLP and computer-vision solutions
• Participate in model versioning, monitoring, deployment, and performance tuning
• Translate business requirements into development tasks
• Integrate AI/ML services via API development and testing
• Write data-processing scripts and automate workflows
• Contribute to web applications, database operations, and system maintenance
• Participate in code reviews and apply best practices
• Deploy projects on AWS, Azure, or GCP
• Configure and customize CRM/ERP platforms (e.g., HubSpot, Salesforce)
• Support IT initiatives: system integrations, data migrations, workflow automation
• Develop Python/SQL pipelines for data preparation
• Implement data-quality checks and validation
• Assist with CI/CD testing and deployment workflows
• Contribute to data governance and security protocols
• Attend AI/ML workshops and training sessions
• Engage in team meetings, project planning, and client presentations
• Document processes, share knowledge, and present project outcomes