BlackBox Hiring for AI Intern Role. Interested Candidates can go through the details and apply using the link provided at the bottom of the Post.
BlackBox – AI Intern
| Company name | BlackBox |
| Website | www.BlackBox.com |
| Job Role | AI Intern |
| Work Location | India |
| Job Type | Full Time |
| Experience | Freshers |
| Qualification | Bachelor/master’s degree |
| Batch | Not Mentioned |
| Package | As Per Company Standards |
Job Description
BlackBox – AI Intern
Job Description
We are seeking an AI Engineer Intern to contribute to the design, integration, and deployment of advanced AI systems. The role will focus on Generative AI, Large and Small Language Models (LLMs/SLMs), and prompt engineering to support conversational AI and workflow automation. You will collaborate with senior team members to implement scalable AI solutions, manage smooth deployments, and expand AI applications across business functions. This internship provides an excellent opportunity to gain practical experience in building enterprise-ready AI solutions.
Key Responsibilities
AI Solution Development
- Data Engineering: Build and manage data pipelines, including extraction, transformation, and loading (ETL), while preparing datasets for AI model training and consumption.
- Model Integration: Incorporate large language models (e.g., GPT, BERT) and retrieval-augmented generation (RAG) approaches, primarily leveraging Azure AI platforms, to deliver context-aware outputs.
- Backend Services: Create secure and scalable APIs and backend systems to support deployed AI models.
- Frontend Collaboration: Assist in developing user interfaces that connect end-users with AI solutions, ensuring usability and alignment with UI/UX standards.
Documentation & Knowledge Transfer
- Handover Preparation: Prepare detailed solution documentation to support transition from vendors or internal teams.
- Team Collaboration: Actively participate in cross-functional discussions and share knowledge to align model development with deployment goals.
Quality Assurance
- Testing Protocols: Design tests to confirm model accuracy, stability, and performance.
- Automation: Implement automated workflows for testing pipelines, data handling, and user-facing features.
- Debugging: Identify and resolve issues, while documenting solutions to maintain quality standards.
Deployment & Operations
- Production Readiness: Manage the deployment of AI models into production using Azure tools and frameworks.
- Monitoring: Establish monitoring systems to track performance and reliability of deployed models.
- Lifecycle Management: Oversee solution lifecycle, including versioning, retraining, and decommissioning processes.
Innovation & Growth
- Continuous Learning: Stay updated on the latest AI advancements, especially RAG methods and Azure capabilities.
- Initiative: Recommend improvements to processes and propose creative solutions.
- Ownership: Take responsibility for assigned projects, managing development, testing, and deployment with independence.
Required Skills
Technical Skills
- Proficiency in Python for AI and data-related development.
- Experience with Azure AI services and deployment frameworks.
- Knowledge of ETL pipelines and data preprocessing techniques.
- Understanding of backend frameworks such as Flask or Django, including API development.
- Familiarity with testing frameworks and automated QA processes.
Soft Skills
- Ability to work independently and take initiative.
- Strong written and verbal communication for documentation and collaboration.
- Flexibility to adapt to different aspects of AI solution development.
- Problem-solving mindset with enthusiasm for tackling technical challenges.
Preferred Skills
- Exposure to Retrieval-Augmented Generation (RAG) methods.
- Knowledge of prompt engineering for improving generative model outputs.
- Experience with predictive modeling techniques such as supervised and unsupervised learning.
- Familiarity with frontend frameworks (React, Angular, Vue, or Typescript) and UI/UX integration.
- Understanding of cloud computing concepts, especially in Azure.
- Awareness of Generative AI models and Natural Language Processing (NLP).
- Ability to create structured documentation and basic understanding of compliance in AI practices.
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About BlackBox
BlackBox AI is an AI-powered coding assistant designed to help developers write, understand, and optimize code more efficiently. It can generate code snippets, explain existing code, and provide real-time suggestions across multiple programming languages. The tool integrates with popular development environments, making it easier for programmers to streamline workflows, reduce errors, and accelerate software development. Its strength lies in simplifying complex coding tasks and boosting productivity for both beginners and experienced developers.