AI/ML Engineer Intern
Build the models that power our enterprise AI platform
The Role
You will work directly on our AI platform — building, training, and deploying models that power real enterprise workflows. This is not a research-only role. You will ship code that runs in production and impacts paying customers.
Depending on your strengths, you could work on:
- Inferova Parse — Document intelligence: OCR, layout understanding, table extraction, field classification
- Hariyaalee — Computer vision for agriculture: plant disease detection, yield prediction, environmental monitoring
- Inferova Sonics — Voice AI: speech-to-text, NLU pipelines, conversational agent design
- LLM Studio — Fine-tuning and deploying custom language models, evaluation frameworks, inference optimization
What You'll Do
- Build and improve ML pipelines — data preprocessing, model training, evaluation, deployment
- Work with real enterprise datasets (documents, images, audio, text)
- Optimize model performance for accuracy, latency, and cost
- Write clean, production-ready Python code with proper testing
- Collaborate with product and engineering teams to ship weekly
- Read papers, prototype ideas, and benchmark against existing approaches
Must Have
- Currently pursuing or recently completed B.Tech/M.Tech/MS in CS, AI/ML, or related field
- Strong Python fundamentals
- Hands-on experience with at least one of: PyTorch, TensorFlow, or HuggingFace Transformers
- Understanding of core ML concepts — supervised/unsupervised learning, CNNs, transformers, loss functions, evaluation metrics
- Ability to read and implement ideas from research papers
- Git proficiency
Good to Have
- Experience with computer vision (OpenCV, YOLO, segmentation models)
- Experience with NLP/LLMs (fine-tuning, prompt engineering, RAG)
- Experience with speech/audio ML (Whisper, TTS models)
- Familiarity with MLOps tools (MLflow, Weights & Biases, Docker)
- Contributions to open-source ML projects
- Kaggle or competitive ML experience
Why Join Us
- Work across platform capabilities — not just one narrow problem
- Ship to production from week one, not months of onboarding
- Direct access to the founding team and customers
- Learn how to build AI products that people actually pay for
- Strong performers get a full-time offer