onsite
Junior AI/ML Developer
Junior AI/ML Engineer Intern
The Junior AI/ML Developer will join Drishti IAS's EdTech innovation team to build, fine-tune, and deploy AI models for conversational learning agents and intelligent tutoring systems. Key responsibilities include optimizing LLM inference pipelines, integrating AI frameworks like Hugging Face and LangChain, developing RAG systems, and contributing to multimodal AI solutions.
About the role
Role Overview
We are seeking a passionate AI/ML Developer with 1–2 years of hands-on experience to join our EdTech innovation team. You’ll work on building, fine-tuning, and deploying AI models that power conversational learning agents, intelligent tutoring systems, and generative educational content platforms.
Key Responsibilities
- Model Development & Inference
- Build and optimize LLM inference pipelines for scalable performance (TPS/RPS optimization).
- Experiment with BLEU scores, re-ranking models, and evaluation metrics for NLP/NLG tasks.
- AI/ML Integration & Frameworks
- Work with frameworks such as Hugging Face Transformers, LangChain, and OpenAI/Anthropic APIs.
- Develop agentic RAG (Retrieval-Augmented Generation) systems for contextual learning applications.
- Integrate Vector Databases (Pinecone, FAISS, Milvus) for semantic search and content retrieval.
- Conversational & Multimodal AI
- Build voice-based conversational agents with TTS/STT integration for multilingual learning assistance.
- Implement OCR and Vision APIs for content digitization and visual learning analysis.
- Contribute to multimodal AI systems combining text, speech, and visual data.
- Model Optimization & Deployment
- Conduct fine-tuning and transfer learning on educational datasets.
- Focus on cost-efficient AI deployment and model serving in production environments.
- Use MLOps tools (MLflow, Vertex AI, or SageMaker) for pipeline automation.
- Compliance & Ethics
- Ensure all models adhere to AI compliance, data privacy, and ethical use standards within EdTech.
Qualifications
- Bachelor’s or Master’s in Computer Science, AI, Data Science, or related fields.
- 1–2 years of experience in machine learning, NLP, or applied AI.
- Hands-on experience with Python, TensorFlow/PyTorch, and Transformers.
- Familiarity with APIs, REST endpoints, and AI model deployment.
- Basic understanding of metrics like BLEU, F1, and accuracy for model evaluation.
Nice to Have
- Experience with LLM fine-tuning and custom dataset preparation.
- Exposure to AI compliance frameworks (GDPR, FERPA, etc.) in educational contexts.
- Knowledge of agent-based systems and tool-augmented AI agents.
What We Offer
- Opportunity to contribute to impactful EdTech innovations.
- Exposure to cutting-edge AI systems and real-world deployments.
- Collaborative culture with opportunities for upskilling and research.