AI/ML Engineering Intern - Lahore
1 day ago⚠️ Before applying, please carefully review all the job requirements
- Location:
- Lahore, Pakistan
- Work Arrangement:
- Onsite
- Experience:
- Fresher
- Job Type:
- Internship (3-Month Paid)
- Company:
- TAG Solutions (TAGS)
- Salary:
- Negotiable
- Posted:
- 2026-10-02
- Working Hours:
- Flexible
Job Overview
- TAG Solutions (TAGS) is hiring three AI/ML Engineering Interns to join its office in Lahore, Pakistan. This 3-month paid internship is designed for energetic fresh graduates and early-career minds who are eager to build, experiment, and take direct ownership of real-world engineering projects. Working strictly onsite with flexible working schedules, interns will collaborate with the team to develop practical artificial intelligence and machine learning solutions.
- The internship offers a performance-based pathway toward a full-time role, making it a strong opportunity for individuals who want to convert hands-on learning into a long-term engineering career. Selected candidates will gain exposure to project development workflows, experimental prototyping, and team collaboration. This position is ideal for motivated individuals seeking an immersive engineering environment where initiative and technical curiosity are valued over routine task completion.
Key Responsibilities
- ★ Assist in designing, developing, and testing artificial intelligence and machine learning features.
- ★ Collaborate with senior engineers to experiment with new technical solutions and build functional prototypes.
- ★ Take full ownership of assigned engineering tasks and deliver reliable technical outputs.
- ★ Participate in testing and refining software components based on team feedback and project needs.
Required Skills and Qualifications
- ★ Educational background in Computer Science, Software Engineering, or a related technical discipline with an AI/ML focus.
- ★ Strong foundational knowledge and genuine interest in artificial intelligence and machine learning concepts.
- ★ Passion for hands-on problem solving, experimentation, and building practical software products.
- ★ Willingness to work strictly onsite at the Lahore office under flexible working hours.
- ★ Ability to submit a relevant technical portfolio or project repository alongside the resume.
Who May Be a Good Fit for This Role?
- This role may be suitable for candidates who are fresh graduates or early-stage engineering talent looking to launch a career in artificial intelligence and machine learning. It suits proactive individuals who enjoy experimenting with modern technologies, taking responsibility for their code, and applying theoretical knowledge to practical systems. Candidates who thrive in an onsite team setting and are motivated by the prospect of turning a paid internship into a full-time employment opportunity will find this role well-aligned with their goals.
What the Company Offers
- ★ 3-month paid internship program.
- ★ Performance-based career pathway to a full-time engineering position.
- ★ Flexible working hours in an onsite office environment.
Application Tips
- Applicants may want to highlight relevant academic projects, personal coding repositories, or technical experiments focused on artificial intelligence and machine learning. Including links to a GitHub profile, technical portfolio, or project demonstrations in your CV can help showcase your practical building experience. Candidates should ensure their email application strictly follows the required subject line format to ensure smooth review by the hiring team, as walk-in applications are not accepted.
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.
Suggested Interview Questions
- Q: What specific machine learning projects or models have you developed during your studies or personal practice?
- Q: How do you approach learning a new artificial intelligence tool or library when starting a fresh project?
- Q: Can you describe a time when an experiment or code implementation failed and how you resolved it?
- Q: How do you evaluate the performance and accuracy of a machine learning model you have built?
- Q: What does taking ownership of an engineering task mean to you in a team setting?
- Q: How do you organize your workflow when working on flexible schedules in an office environment?
- Q: Which programming languages and machine learning frameworks are you most comfortable using?
- Q: How do you prepare a project repository or technical portfolio to showcase your engineering work to others?
To apply, send your CV and relevant portfolio (where applicable) via email to: hr@tagsolutionsltd.com
