Machine Learning – Internship (WFH) at NDFM Business World Pvt. Ltd.
NDFM Business World Pvt. Ltd. is accepting applications for a paid, work-from-home Machine Learning internship. The opportunity combines model development, dataset preparation and the integration of machine-learning solutions into applications. It is a short internship lasting four weeks, with an advertised stipend of ₹5,000–6,000 per month. The live listing shows seven openings and an application deadline of 7 November 2026.
There is an important scheduling detail: this is not advertised as an immediate-start internship. Applicants must be able to begin between 1 December and 31 December 2026. If you are looking for a remote opportunity that fits into your December calendar, check both the start window and the four-week commitment before applying.
Opportunity overview
| Employer | NDFM Business World Pvt. Ltd. |
|---|---|
| Role | Machine Learning Intern |
| Work mode | Work from home |
| Duration | 4 weeks |
| Advertised stipend | ₹5,000–6,000 per month |
| Start window | 1–31 December 2026 |
| Apply by | 7 November 2026 |
| Openings | 7 |
| Required skills | Python, Machine Learning and Deep Learning |
What the intern will work on
The responsibilities cover three connected stages of machine-learning work. The first is developing models: designing, training and implementing solutions using Python, machine-learning algorithms and modern frameworks. The listing does not name a particular framework, so applicants should not assume that experience with one specific library is mandatory.
The second stage focuses on data and performance. Interns are expected to collect, preprocess and analyse datasets, evaluate model results and work on improvements in accuracy, efficiency and scalability. This makes the opportunity relevant to someone who wants practical exposure beyond running a model once: the stated work includes preparing inputs and assessing whether the resulting solution performs well.
The third stage involves collaborating with development teams to integrate models into real applications. Testing and support for deployment are also mentioned. The advertisement does not identify a particular product, dataset, cloud provider or industry use case. Those details can be discussed with the employer during the application process rather than treated as confirmed features of the internship.
Eligibility and availability
The published eligibility conditions are straightforward. Candidates must be available for a work-from-home internship, be able to start within the December window, commit to four weeks, and have relevant skills and interests. Python, Machine Learning and Deep Learning are the skills named in the listing.
No specific degree, minimum marks, graduation year, age limit or previous-employment requirement is stated in the complete live opportunity details. That does not mean selection is automatic or that every applicant will meet the employer’s expectations. It means applicants should use the stated skills and availability conditions to judge their fit, without relying on an invented academic cutoff.
For a short remote assignment, it is useful to check whether examinations, classes or another commitment would prevent you from participating during December. The listing offers flexible work hours but does not specify daily hours, working days or meeting times. Ask about those arrangements before accepting an offer, especially if you need to combine the internship with college.
Stipend, duration and perks
The stipend is advertised as ₹5,000–6,000 per month. Because the internship lasts four weeks, the monthly figure should not be rewritten as a guaranteed total payout. The listing does not explain how the exact amount within the range is determined, when payments are made or whether any proration applies. Confirm those terms with the employer if selected.
A certificate, a letter of recommendation and flexible work hours are listed as perks. These are the benefits expressly mentioned; the opportunity does not advertise a guaranteed permanent job or a conversion package. Keep a distinction between the current internship and any future employment discussion.
Preparing a relevant application
The following preparation suggestions are guidance, not additional employer eligibility rules. If you have completed a Python or machine-learning project, describe the problem, the data preparation, the model you used and the way you evaluated its output. A clear explanation of your own contribution is more helpful than a long list of tools with no supporting work.
You could include a readable repository or portfolio link if you already have one, making sure it contains no private data or credentials. Since the responsibilities include collaboration and deployment support, be ready to explain how your work can be understood or reused by another developer. Do not claim production deployment experience if your project was only a classroom exercise.
How to apply
- Open the live Internshala listing linked below and read the latest terms.
- Check the four-week duration, December start window and advertised stipend against your availability.
- Use the listing’s Apply now option and complete the application through Internshala, signing in if the platform requires it.
- Provide accurate skill and project information and retain any application confirmation.
The employer’s listed profile location is Amritsar, but this particular internship is explicitly work from home. Do not confuse the company’s profile location with an in-office requirement. Selection stages and payment arrangements are not described in the advertisement; confirm them through the employer’s authorised communication if your application progresses.
Read the complete listing and apply for the NDFM Machine Learning internship. Applications are advertised until 7 November 2026; check the live page for any subsequent change before submitting.
