Stratnova Technologies Data Science & AI/ML Engineer – Internship (WFH)
Stratnova Technologies has advertised a paid, work-from-home Data Science & AI/ML Engineer internship on Internshala. The programme lasts three months and lists a monthly stipend of ₹20,000–50,000. There is one opening, with applications advertised until 7 November 2026. The live listing was marked as posted one day ago when checked for this batch.
This is a technically substantial internship rather than an introductory course with an internship label. The employer asks for evidence of hands-on AI/ML work, a relevant quantitative degree background, and strong Python, SQL and statistics skills. Candidates should read those requirements alongside the attractive advertised stipend before deciding whether to apply.
Important details at a glance
- Employer: Stratnova Technologies
- Opportunity: Data Science & AI/ML Engineer internship
- Work mode: Work from home
- Duration: Three months
- Stipend: ₹20,000–50,000 per month, as advertised
- Vacancies: One
- Application deadline: 7 November 2026
- Joining window: 8 October–12 November 2026
The stipend is a range, not a guarantee that each applicant will receive ₹50,000. The listing does not explain how an offer within that range is determined. It also does not disclose a fixed daily timetable, weekly working days or guaranteed conversion package. Applicants should clarify any such terms with the employer during the hiring process.
Machine learning and language-focused work
The responsibilities begin with building and testing machine-learning models. Examples named by the employer include classification, regression, clustering, ranking, recommendation and predictive models. The listing stresses choosing an appropriate approach rather than selecting the most complicated model simply for its complexity.
Natural language processing is another significant area. The intern may work on text classification, intent detection, embeddings, semantic search and conversation analysis. Hindi, Hinglish and multilingual data are explicitly mentioned, so candidates with relevant language-data projects may have useful evidence to discuss in an application.
The generative-AI responsibilities include evaluating and benchmarking LLMs, trying prompts, and working with retrieval-augmented generation and fine-tuning. The source also highlights trade-offs between cost, speed and quality. This indicates that the role considers practical product behaviour, not just whether a model can produce an impressive isolated example.
Evaluation, experimentation and production
Measuring performance is a separate part of the job. The employer names test datasets, precision, recall, F1, human evaluation, error analysis and A/B testing. Applicants should be ready to explain how they evaluated their own projects, including where a model failed or where a baseline remained competitive.
The internship also involves analysing user behaviour, including what users ask, where they drop off and signals associated with engagement. Personalisation work can include segmentation, recommendations, content personalisation and ranking. These tasks connect technical analysis with product decisions without changing the role into a generic marketing internship.
Statistics and reliable data preparation matter throughout the work. Responsibilities include hypothesis testing, statistical significance, distinguishing correlation from causation, handling missing values and outliers, and preventing data leakage. The employer also describes collaboration with engineers to move models from notebooks into production, including monitoring, drift tracking and retraining.
Who should consider applying?
Applicants must be available for remote work, able to start within the stated joining window and available for the full three-month duration. They also need relevant skills and interests. The listed technical skills are data science, generative-AI tools, LLM evaluation, machine learning, mathematics, Python, SQL and statistics.
The other-requirements section asks for a degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a similar field. It also asks for proof of hands-on work, such as strong GitHub projects, Kaggle work, research papers or independent AI/ML builds. Familiarity with Hindi, Hinglish or multilingual NLP is described as a significant plus because the listing says Aura AI’s data is heavily language-based.
As practical application advice, select a small number of relevant projects and explain your contribution, data preparation, evaluation method and result. Do not claim production deployment or research experience that you do not have. This advice is preparation guidance, not an additional formal eligibility requirement imposed by Jobsii.
Employer context and remote terms
Stratnova describes its business as software development, digital marketing and talent acquisition, with work in AI/ML, cloud-powered software and web/mobile development. The company profile names multiple business locations, but the internship itself is explicitly advertised as work from home. A profile city should not be read as an in-office requirement for this opportunity.
Application process
Use the exact Internshala listing below to review the current opportunity and submit an application through the platform. Check the technical requirements, three-month commitment and joining window before applying. The source does not specify a fixed assessment sequence, so do not assume that selection will follow a particular interview or coding-test format.
Read the Stratnova internship listing and apply
The advertised last date is 7 November 2026. Confirm availability and the final offered terms on the live listing and with the employer before accepting an internship.
