AI Developer Intern
8h ago⚠️ Before applying, please carefully review all the job requirements
- Location:
- NASTP 2, Shahrah-e-Faisal, Karachi
- Experience:
- Fresher
- Job Type:
- Internship
- Company:
- InovioTech
- Salary:
- Paid
- Posted:
- 2026-10-13
- Working Hours:
- Monday to Friday, 8:00 PM – 5:00 AM
- Duration:
- 8 weeks
Job Overview
- This listing from InovioTech is for a *AI Intern* position in NASTP 2, Shahrah-e-Faisal, Karachi. The position is listed as internship. The listed schedule is Monday to Friday, 8:00 PM – 5:00 AM. The stipend mentioned in the listing is PKR 100,000. The listing places its emphasis on REST APIs, Python, Artificial Intelligence and LLMs. For general context: REST APIs let the front end and back end of an application exchange data in a structured way. Artificial intelligence is increasingly part of everyday software products. Read the details below carefully and use the application link on this page if the role matches your profile.
What These Requirements Mean in Practice
- ★ REST APIs: Designing and consuming HTTP endpoints so a front end, mobile app or another service can exchange data.
- ★ Python: Writing readable scripts and backend or data code using Python's standard library and common packages.
- ★ Artificial Intelligence: A general understanding of how AI systems learn from data, where they are useful, and where they can be unreliable.
- ★ LLMs: Understanding how large language models generate text from prompts, and why their output still needs to be checked.
- ★ Generative AI: The concepts behind systems that generate text, images or code, and how such features can be added to a product.
Skills to Brush Up Before Applying
- ★ REST APIs: HTTP methods and status codes, authentication basics such as tokens, validation and error responses
- ★ Python: core data structures, functions and modules, virtual environments and pip
- ★ Artificial Intelligence: supervised versus unsupervised learning, common real-world use cases, limitations and bias
- ★ LLMs: prompting basics, context limits and hallucinations, using an LLM API
- ★ Generative AI: common model types, prompt design, responsible use
Who May Be a Good Fit for This Role?
- This role may be suitable for candidates who are at the start of their career, such as recent graduates or final-year students, and want hands-on exposure to real projects. Those who are comfortable with REST APIs, Python, Artificial Intelligence and LLMs and enjoy building practical projects may find the requirements a good match. This is editorial guidance only, and the employer makes the final decision on suitability.
What You Will Do
- ★ Support AI integration across internal workflows
- ★ Work with AI tools, APIs, automation platforms, and prototypes
- ★ Test and improve AI-powered solutions
- ★ Assist with research, documentation, and implementation
Preferred Skills
- ★ Basic Python, APIs, Generative AI, LLMs, or automation tools
- ★ A strong willingness to learn
How To Apply
- ★ Subject Line: AI Intern
Application Tips
- Applicants may want to highlight relevant experience with REST APIs, Python, Artificial Intelligence and LLMs in their CV. If you have used AI tools or built small projects with language models, briefly describe what you built and how you checked the results. If you have limited work history, academic projects, personal builds, and open-source contributions can demonstrate practical ability. Since applications are sent by email, use a clear subject line that includes the role title and keep your message short, with your CV attached. A short, role-specific summary at the top of your CV usually reads better than a generic profile. These are general tips, not requirements stated by the employer.
Prepare for Your Interview
- These suggested questions can help you prepare for an interview by focusing on the skills, responsibilities, and technical areas relevant to this role. They are for preparation only and are not confirmed employer questions.
- Q: How would you handle authentication and input validation for a REST API you are building?
- Q: How do lists, tuples, sets, and dictionaries differ in Python, and when would you use each?
- Q: Where could AI add value to a typical web application, and what risks should you plan for?
- Q: How would you explain what a large language model is, and where can its answers be unreliable?
- Q: Can you describe a small feature that could use a generative AI API, and how you would integrate it into an app?
- Q: What makes an API RESTful, and how do you choose HTTP methods and status codes for different operations?
- Q: How do decorators and generators work in Python?
- Q: How would you explain the difference between traditional programming and machine learning to a non-technical person?
- Q: What are you hoping to learn in this role, and how have you prepared so far?
Apply by email: recruitment.hr@inoviotech.com