Machine Learning Intern

We’re looking for a Machine Learning Intern who’s excited about building models that solve real Trust & Safety problems at scale. 🚀

As part of the FRND ML team, you’ll train and ship models that help identify fake profiles, unsafe interactions, abusive speech, harassment, spam, and scams on the platform. You’ll work with production data alongside experienced engineers, and the models you build will run on live traffic, not just in a notebook. ⚡

If you enjoy working with data, training models, and seeing your work make real decisions for millions of users, this is a great opportunity to kick-start your ML journey! 🚀

🛠️ What You’ll Do

• 🖼️ Work on image & video ML - fake-profile detection, and spoofed-camera detection on 1:1 video calls.
• 🎙️ Work on audio ML - abuse and unsafe-speech classification, multilingual and code-mixed ASR for audio rooms.
• 💬 Work on text ML - harassment, spam, and scam detection across chat in Hindi, English, and regional languages.
• 📊 Build and clean datasets from production signals and moderation reports, and help define labelling guidelines.
• 🧠 Train and fine-tune models in Python with PyTorch - including vision backbones, audio encoders, and transformer-based text models.
• 🎯 Evaluate models with a production mindset - precision at fixed recall, per-language performance, and the real cost of false positives.
• ⚙️ Collaborate with backend engineers to turn models into inference services and monitor latency and throughput in production.
• 🔍 Monitor model drift, review misclassifications with the moderation team, and improve models through better data and retraining.
• 🤝 Explore LLMs for labelling, policy classifiers, and model evaluation.
• 💻 Write clean, reproducible code and maintain well-documented experiments.

🔎 What We’re Looking For

• 🏢 Available for a 6-month, in-office internship.
• 🎓 Strong academic background from a Tier 1 institution, preferably IITs, BITS, NITs, or equivalent institutions.
• ⭐ High performers may be considered for a PPO based on performance.
• 🎓 Pursuing a degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• 🐍 Strong Python skills and solid programming fundamentals.
• 🔥 Working knowledge of PyTorch or TensorFlow - you’ve trained models yourself.
• 📚 Strong understanding of ML fundamentals - overfitting, regularisation, train/validation/test hygiene, precision vs. recall.
• 📈 Comfortable with NumPy, pandas, and notebooks for data work.
• 👁️ Projects in computer vision - CNNs, ViTs, classification/detection - are a plus.
• 🎧 Exposure to audio ML - spectrograms, ASR, Whisper, or wav2vec-style models - is a plus.
• 💬 Experience with NLP, transformers, or Hugging Face is a plus.
• 🛠️ Basics of SQL, Git, or Docker are a plus.
• 🛡️ Interest in Trust & Safety, content moderation, or responsible AI is a plus.
• 🚀 Curiosity, ownership, and a strong willingness to learn.

The FRND team operates 6 days a week, with the 1st and 3rd Saturday being working Saturdays.

About FRND

FRND is redefining the way people connect by building social products that are engaging, safe, inclusive, and fun.

We’re a rapidly growing startup building for millions of users and solving unique challenges across social connection and entertainment. Our ambition is bold, and we're looking for people who want to build, experiment, and solve problems at scale.

Why FRND?

🌍 Impact at Scale: Work on products and initiatives that impact millions of users across India and international markets.

🚀 High Ownership: Take on meaningful problems and have the freedom to drive them from idea to execution.

🧠 Learn with the Best: Work closely with founders, leaders, and high-performing teams while solving real business challenges.

💼 Rewarding Journey: Competitive compensation, equity opportunities, and growth that matches your impact.

🎉 Work Hard, Have Fun: We're serious about building great products, but we also believe in enjoying the journey along the way.

💡 Solve Interesting Problems: Work in an environment where curiosity, experimentation, and first-principles thinking are encouraged.