Posted 14h ago
Deep Learning Research Internship
Posted 2d agoBe an early applicant
What this role pays, in context
This listing pays 8% below the median for Data Scientist roles in India, which sits at ₹25K a month.
25th pct ₹20.3K75th pct ₹27.3K
Median of 11 other live Data Scientist listings in India on this board that state pay. Roles that do not disclose a salary are excluded rather than counted as zero.
An open question, not a ticket
Can a model tell, from the text of a job post alone, whether the compensation it advertises is plausible for that role in that city? Nobody here knows, and over three months you will find out.
Method
You assemble a dataset of Indian internship posts, build a text regression baseline in scikit-learn using TF IDF, then move to a fine tuned transformer from Hugging Face and test whether the extra capacity earns its keep. You report mean absolute error broken out by city and by domain rather than as one headline number, because the aggregate hides exactly the failure mode you care about. Ablations, multiple seeds and an honest limitations section are all expected. If the work holds up, it becomes a trust signal on the live site.
Support and setting
You work from the Mumbai office three days a week, with GPU access and a weekly one to one with the research lead. There is a reading group on Wednesdays, and you will present a paper at least once. Final year students and recent graduates are welcome. Coursework level deep learning and a willingness to be wrong in public are the real requirements here.
Responsibilities
- Assemble a dataset of Indian internship posts and clean its labels
- Build a TF IDF text regression baseline before touching anything larger
- Fine tune a transformer checkpoint from Hugging Face and compare it honestly against that baseline
- Report error broken down by city and domain rather than as a single headline figure
- Run ablations across multiple seeds and document what did not work
- Present a paper to the Wednesday reading group at least once
- Write up limitations clearly enough that the team can act on them
Requirements
- Final year student or recent graduate in CS, electrical engineering, statistics or a related field
- Python and PyTorch at coursework level
- Familiarity with gradient descent, regularisation and overfitting
- Comfortable reading a research paper and summarising its method out loud
- Available three days a week in Mumbai across three months
Skills
Benefits
- Monthly research stipend
- GPU access and a weekly one to one with the research lead
- Wednesday reading group and a conference ticket if your work is accepted
- Internship certificate and a detailed reference from the research lead