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Machine Learning Intern

Machine Learning Intern

WadhwaniAI LEHSDelhi, DL, in
19 days ago
Job type
  • Quick Apply
Job description

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

  • Good at AI / ML fundamentals
  • Good at LLM fundamentals like RAG-QA, Prompt Engineering, Evaluations, Vector Stores, Retrievals and Chunking, Fine-tuing, Synthetic data generation, model deployment, etc.
  • Experience with GenAI tools (but not limited to) like LangChain, LlamaIndex, LlamaParse, Langfuse, FAISS, Chroma, vLLM, OpenAI toolkits and SDK, etc.
  • Familiarity with OpenAI models and tools, Open-source LLM models like gpt-oss, Llama, Gemma, Mistral, Wave2Vec2, Bhashini's or AI4Bharat's language translation model, etc.
  • Familiarity with Docker, AWS, GCP is a plus
  • Strong Python coding and debugging skills, hands-on experience with some of the Data Science toolkits like Pandas, Numpy, Matplotlib / Seaborn, etc. and preferably at least one Deep Learning Framework among Pytorch (preferably), Keras, TensorFlow, etc.
  • Should have completed coursework in Probability, Linear Algebra, Calculus and preferably has some exposure to AI / Machine Learning.
  • Highly preferred to have demonstrated experience of working in the field via an internship or project. Do provide links to some of your open-source projects.
  • Prior exposure to Linux / Unix is expected before joining for the internship.

    • 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

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