Work From Home | Internship Certificate | Mentorship (During & After Internship) | Join a Team of 10 | Flexible Hours | IST Timezone
We support 5 apps across Web, iOS, and Android.
Join a dynamic team supporting a suite of 5 applications across Web, iOS, and Android. We utilize a modern stack—Expo/React Native for frontend, Node.js/MongoDB for backend, and AWS for infrastructure. We are now embedding AI/ML capabilities into our products to deliver smarter user experiences.
About the Internship
Are you passionate about building intelligent systems and eager to apply machine learning to real-world, cross-platform applications? We are looking for an AI/ML Intern to help us integrate predictive features, automate decision-making, and extract insights from user data.
You will gain hands-on experience in:
Data Engineering: Collecting, cleaning, and labeling data from our backend (Node.js/MongoDB) and user interactions across Web/iOS/Android.
ML Deployment: Packaging and deploying models as microservices on AWS (Lambda, SageMaker, or ECS) and exposing them via REST APIs.
Integration: Working with our React Native and Node.js teams to embed AI features (e.g., smart search, personalization, anomaly detection) into live apps.
Model Development: Building and fine-tuning ML models (classification, regression, recommendation, or NLP) using Python and modern frameworks.
You will work alongside experienced mentors, receive an Internship Certificate, and contribute to impactful projects.
What We Offer
Deep Technical Growth: From understanding ML theory to production-ready deployment on AWS.
Mentorship: Direct guidance during and after the internship – including code reviews, model tuning sessions, and career advice.
Exposure: Full-stack visibility – Frontend, Backend, DevOps, and now AI/ML.
Career Path: After 3 months of paid internships, you are eligible to apply for paid full-time AI/ML or full-stack roles within the team.
(Note: 4 out of 12 interns from our Jan 2025 cohort transitioned to full-time in July.)
Requirements
Technical Skills:
Strong logical reasoning and a problem-solving mindset.
Proficiency in Python (required); familiarity with JavaScript/TypeScript is a plus.
Basic understanding of ML concepts (supervised/unsupervised learning, evaluation metrics, overfitting).
Experience with at least one ML framework: TensorFlow, PyTorch, or Scikit-learn.
Familiarity with data manipulation (Pandas, NumPy) and REST APIs.
Exposure to AWS (S3, Lambda, or SageMaker) or MongoDB is a significant plus.
Availability:
Able to join daily sync-ups at 7 AM IST.
Open to working on Saturdays.
Commitment of ~5 hours per day.
Must have less than or equal to 4 hours of daily college/travel commitments to ensure focus.
Available for a 3-month duration; can join within 1 week.
Responsibilities
Data Pipeline: Assist in collecting, cleaning, and annotating datasets from our 5 apps (web + mobile).
Model Building: Implement and train ML models for use cases like user behavior prediction, content recommendation, or image/text classification.
Evaluation: Measure model performance, run A/B tests, and iterate to improve accuracy and latency.
Integration: Wrap models into simple APIs (using Flask/FastAPI) and collaborate with backend engineers to ship features.
Monitoring: Track model drift and data quality in production, suggest retraining schedules.
Documentation: Write clear, reproducible notebooks and technical guides for future interns.
Hiring Process
Offline Coding/Logic Exercise (3–10 hours)
A task focused on data manipulation, a simple ML model, or a logic puzzle relevant to AI/ML.
Live Debugging/Coding (GMeet) (1–3 hours)
Modify and discuss your solution in a live session – we’ll test your understanding of the code and ML concepts.
Final Interview (30 minutes)
Phone round with our CEO to discuss your motivation, learning goals, and fit.
Note: We respect your time. If our rigorous 0.3% selection rate or the effort required feels excessive for this role, we encourage you to apply elsewhere. We provide constructive feedback to those who reach the live round but are not selected.
How to Apply
This role is for those who want to build a career in applied AI/ML engineering or ML-driven product development.
You will gain significant experience working on real-world projects, from data wrangling to production deployment. Pre-Placement Offers (PPOs) may be extended to exceptional interns in the final month, based on performance, team needs, and company capacity. The 5 paid team members we have now were all interns earlier.
After 3 months of internship, you get to apply for paid full-time roles within the team.
Source: Wellfound.
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