Machine Learning Intern

Job Description

This is a remote position.

• Conduct experiments and reports results reliably, with guidance
• Experiments includes (but not limited to) :
• Benchmark open-source LLMs (gpt-oss-120 / 20b, Llama models, etc.) against the proprietary LLMs (like OpenAI's GPT-4o / -mini, Gemini, etc.)
• Experiment with LLMs to create the scalable and search-efficient KB, synthetic QA generation from the digital documents, and Prompting optimizations to build the scalable chatbots
• Evaluate language translation models / services for Indian languages (e.g., Bhashini, Sarvam, Google Translate, etc.)
• Assess Speech models for Indian languages for ASR (STT) and TTS tasks (e.g., Amazon Polly, AI4Bharat's Conformers, Sarvam, etc.)
• Improve the existing RAG-QA pipeline by finding performance gaps, benchmark different Retrieval (Embedding) and chunking techniques
• Gather, clean, analyze, and process the text and speech data for building the knowledge base (KB) for conversational chatbots.
• Learns to derive insights from experiments and next steps
• Watches incoming data regularly and performs quality checks
• Collaborates with cross-functional teams to complete tasks on time
• Proactively seeks help and required information from peers
• Communicate the research findings in a clean and compact manner
• Supports development of good and clean codebases with  documentation of code and work consistently with high standards
• Communicates and presents results effectively with peers
• Stay updated with recent advancements in GenAI-LLMs, ASR (STT and TTS), RAG-QA, Evaluation of LLMs, etc. (that can be applied in our product)
• Develops expertise with typical ML tooling such as Pandas, ML frameworks (Pytorch, Scikit-Learn), Excel (Pivot tables), Visualization libraries, Experiment monitoring (Weights & Biases), GitHub
• Learns to work efficiently with tooling : Unix, VSCode, Google office suite, Calendar, Slack
• Ability to work in a fast-paced startup environment
• Eagerness to learn, and apply the latest research / work happening in the domain in the solution

Requirements

Requirements

M.Tech. / M.E. / M.S. / M.Sc. or equivalent in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics, Economics, or a relevant quantitative field