AI/ML – Internship (WFH)
Codeatrix has advertised ten openings for a two-month work-from-home AI/ML internship. The listing focuses on practical projects, datasets, Python, basic machine-learning models and mentor-guided work. The application deadline is 22 November 2026.
The advertised ₹12,000–25,000 monthly total is made up of ₹10,000–20,000 fixed pay and ₹2,000–5,000 incentives per month. The incentive component must remain separate from fixed compensation; the maximum total is not an unconditional fixed stipend.
Internship at a glance
| Employer | Codeatrix |
|---|---|
| Work mode | Work from home — India |
| Duration | 2 months |
| Stipend | ₹10,000–20,000 fixed + ₹2,000–5,000 incentives/month |
| Apply by | 22 November 2026 |
| Openings | 10 |
| Original posting date | 2026-10-23 |
Project responsibilities
Interns will work on AI and machine-learning projects using datasets and problem statements, clean and process data with Python and relevant libraries, and develop, train and evaluate basic models. The description also mentions supervised and unsupervised learning, evaluation and predictive analytics through practical work.
Mentor-guided sessions, assigned tasks and documenting and presenting outcomes are part of the advertised arrangement. This makes a willingness to learn and explain results important. The public description does not identify a guaranteed client deployment, named model architecture or particular production-system access, so those should not be assumed.
Who the visible employer eligibility welcomes
The complete visible listing explicitly welcomes college students from any year, including first-year through final-year students. It also welcomes freshers, recent graduates and candidates with a career gap who want practical experience or a career restart.
Degrees or diplomas in computer science, data science, AI, mathematics, statistics, engineering or related areas are preferred, but the employer's visible text says candidates from any academic background can apply. Basic Python or machine-learning knowledge is preferred rather than mandatory. Candidates should be interested in the subject, willing to learn and ready to complete tasks with mentor guidance.
Applicants must be available for work from home for two months and able to start between 23 October and 27 November 2026. Women starting or restarting their careers are also invited. The named skills include Python, machine learning, Excel, natural-language processing and artificial intelligence.
Stipend, hours and listed benefits
The page advertises flexible working hours and a five-day week, with a certificate and letter of recommendation. It does not mark the role as part-time or specify exact daily hours. Confirm the time commitment and task deadlines before accepting, particularly if you have another full-time commitment.
The public page does not explain the incentive calculation. Ask the employer how performance-linked pay is determined, when it is settled and what fixed amount applies to your offer. Do not treat the top of the advertised range as the amount every selected intern will receive.
Employer context and application preparation
Codeatrix describes itself as a technology-focused learning organisation offering mentor-guided internships and projects across several technology domains, with career and placement guidance. Those services are employer descriptions, not a guaranteed job-placement outcome. The profile is based in Bengaluru, while this specific opening is remote.
Explain your current level honestly. If you have a project, describe its dataset, the question you investigated, how you evaluated the result and one limitation. If you are beginning, explain your relevant coursework or learning interest without claiming professional expertise. Before accepting, confirm supervision, project expectations, hours and written compensation terms. The opportunity should not be confused with a promise of permanent employment.
How to apply
Read the complete employer listing and submit your application through Internshala using the link below. Check the stated joining window and your availability before applying. An application is not a selection or an offer; the employer decides the outcome.
