The EduRankAI Anomaly Detection Engineering internship is now open for applications on the AICTE Internship Portal. It has a performance based stipend and runs for 3 months. EduRankAI has 4 openings. Apply by 30 Nov 2026. EduRankAI posted it on 30 Sep 2026.
The listing does not limit it to one degree or stream. It suits students who want hands-on work with Machine Learning, Statistics and Cyber Security. This post covers the work you will do, who can apply, the stipend, key dates and how to apply, with the official link. Details the listing leaves out are marked as not specified.
Internship Overview
Check these details before you apply.
| Organization | EduRankAI |
|---|---|
| Internship Role | Anomaly Detection Engineering Intern |
| Stipend | Performance Based |
| Location | Not specified |
| Work Mode | Not specified |
| Internship Type | Full Time |
| Duration | 3 Months |
| Openings | 4 |
| Last Date to Apply | 30 Nov 2026 |
| Apply On | AICTE Internship Portal |
About EduRankAI
The listing does not include a profile of EduRankAI. Look up the organization's own website and LinkedIn page to learn about its work before you apply.
Internship Details
EduRankAI is inviting applications for the position of Anomaly Detection Engineering Intern to join our Data Science, Machine Learning, Artificial Intelligence, and Engineering team. Scikit-learn documents Isolation Forest as an unsupervised approach in which observations that can be isolated with shorter tree paths are treated as more abnormal, while its outlier-detection documentation also covers Local Outlier Factor, One-Class SVM, and robust covariance approaches. You may investigate contextual anomalies in which a value is unusual only under a particular time, location, user, machine, or operational context.
You may also investigate collective anomalies, where a group or sequence of observations becomes abnormal even when individual observations may not appear unusual independently. Feature engineering will be an important part of the internship, including statistical aggregates, rolling-window features, ratios, deviations from baselines, frequency-based features, temporal features, behavioral features, and domain-specific indicators. You may use Python, pandas, NumPy, SciPy, scikit-learn, Jupyter Notebook, SQL and Excel.
Roles and Responsibilities
The listing describes the work like this:
This full-time internship is designed for individuals who are passionate about anomaly detection, outlier detection, machine learning, statistical analysis, data science, time-series analysis, predictive analytics and artificial intelligence. As an Anomaly Detection Engineering Intern, you will contribute to developing and evaluating analytical and machine learning approaches for identifying unusual, unexpected, or potentially significant patterns in structured and unstructured data. The internship provides practical exposure to the complete anomaly detection lifecycle, including data collection, data preprocessing, exploratory data analysis, feature engineering, baseline development, anomaly modeling and anomaly scoring.
You may research both supervised and unsupervised anomaly detection techniques depending on the availability of labeled data. The internship will introduce statistical techniques such as z-score analysis, modified z-scores, interquartile range methods, percentile-based detection, robust statistics, probability distributions, density estimation, and statistical thresholding. You may also work with machine learning approaches such as Isolation Forest, Local Outlier Factor, One-Class Support Vector Machines, robust covariance methods, clustering-based detection, distance-based methods, and other anomaly detection algorithms.
The internship may involve developing anomaly detection pipelines that preprocess data, generate relevant features, calculate anomaly scores, establish thresholds, classify observations, and produce alerts or analytical outputs. You may work on threshold optimization by examining anomaly-score distributions, validation datasets, business requirements, false-positive rates, false-negative rates, and operational costs. You may work with moving averages, rolling statistics, exponentially weighted statistics, seasonal decomposition, forecasting residuals, change-point analysis, and machine-learning-based time-series approaches.
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Domains and Departments
- Team: Data Science, Machine Learning, Artificial Intelligence, and Engineering
Eligibility Criteria
You can apply if you match these points:
- Students and graduates from any degree or stream
- The role may involve working with transactional data, sensor data, network data, application logs, financial datasets, industrial data, user activity, IoT streams, time-series data, and other datasets where unusual behavior needs to be identified.
- The internship may also involve IoT anomaly detection, where continuous sensor streams are monitored for abnormal readings, device behavior, or communication patterns.
- You can work full time for the full 3 months
Required Skills
Skills mentioned in the listing:
- Machine Learning
- Statistics
- Cyber Security
- Data Analysis
- IoT
- Python
- Pandas
- SQL
Stipend and Benefits
No fixed amount is given in the listing. We show the stipend as performance based. Ask the company about the amount before you join.
Benefits
- Practical exposure to Anomaly Detection Engineering and Machine Learning
- Hands-on experience with real-world datasets containing normal and abnormal patterns
- Practical learning in outlier detection, novelty detection, and anomaly scoring
- Experience implementing and comparing Isolation Forest, Local Outlier Factor, One-Class SVM, and statistical detection methods
- Exposure to time-series anomaly detection and temporal pattern analysis
- Experience with feature engineering, statistical features, rolling features, behavioral features, and baseline modeling
- Practical learning in threshold selection, threshold optimization, and anomaly-score analysis
- Exposure to cybersecurity, fraud, IoT, industrial, software, and operational anomaly detection use cases
Internship Duration and Mode
The internship runs for 3 months and is full time. The listing does not say whether the work is remote or in the office.
Important Dates
| Posted On | 30 Sep 2026 |
|---|---|
| Last Date to Apply | 30 Nov 2026 |
| Internship Start Date | Not specified |
Required Documents
The listing does not list any required documents. Keep an updated resume in PDF format ready, as most forms ask for one.
Selection Process
The selection process is not described in the listing. Keep checking your email after applying, as shortlisted students are contacted there.
How to Apply for the Anomaly Detection Engineering Internship
- Tap "Apply Now" below to open this internship on the AICTE Internship Portal.
- Sign in to the portal. First-time users need to register as a student.
- Read the details once more, then click Apply and answer the questions the company asks.
- Check your portal dashboard and email for updates on your application.
Important Official Links
- Official listing and application: Anomaly Detection Engineering internship listing on the AICTE Internship Portal
- AICTE Internship Portal: internship.aicte-india.org
- EduRankAI website: not given in the listing
This post shows a shorter version of the description; the full text is in the listing above.
Practical Tips for Applicants
- Complete your AICTE Internship Portal profile (college, course and year) before you apply, so the form goes through in one go.
- Add your GitHub link with 1-2 small projects. It matters more than marks for tech roles.
- Match your resume to this listing: put the skills it asks for near the top.
- Do not wait for the last day. Some companies stop taking applications once they have enough.
- Before an interview, spend ten minutes reading about EduRankAI on its website and LinkedIn.
More Internships and Guides
Frequently Asked Questions
Short answers to what students usually ask about this role.
1How much does the EduRankAI Anomaly Detection Engineering internship pay?
The stipend is performance based. The company has not shared a fixed monthly amount.
2Who is eligible to apply?
There is no degree limit. Students and graduates from any course can apply.
3When does the application close?
The last day to apply is 30 Nov 2026. There are 4 seats in total.
4How do I apply for this internship?
Open the listing with the Apply Now button, sign in to the AICTE Internship Portal and submit your application there.
5Is there any fee to apply?
The listing mentions no fee. A real internship never needs a payment to apply or to join.
Conclusion
This Anomaly Detection Engineering role at EduRankAI is a full time internship with a performance based stipend, lasting 3 months. Apply through the official listing before the last date, and confirm the latest details there first.
About the Author
Disclaimer: This article is for information only. AICTE Internship Help Desk is an independent informational website and is not affiliated with AICTE or EduRankAI. Check the latest eligibility, stipend, deadlines and application details on the official website before you apply.
