Kannada Translator

Job Description

Key Responsibilities: Data Set Creation: Develop high-quality, multilingual data for training large language models (LLMs), ensuring linguistic diversity and cultural relevance in Indian languages. LLM Evaluation: Conduct rigorous evaluation of NLP models and AI language models. Benchmark model performance against internal and external systems to ensure accuracy, relevance, and coherence. Supervised Fine-Tuning (SFT) & RLHF: Apply supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) techniques to improve model performance and adapt to specific tasks. Model Benchmarking: Perform benchmarking of AI models to ensure that Krutrim’s LLMs perform competitively in real-world applications. Model Response Evaluation: Evaluate the quality of model responses across various tasks and benchmarks. Ensure alignment with desired output accuracy, contextual understanding, and linguistic precision. Collaboration with Cross-Functional Teams: Work closely with data scientists, engineers, and AI researchers to integrate linguistic insights and optimize machine learning models for Indian languages. Desired Skills & Qualifications: Linguistic Expertise: Native-level fluency in one or more Indian languages, with excellent command over English. Proficiency in multilingual linguistics is a plus. AI & NLP Knowledge: Strong understanding of Natural Language Processing (NLP), machine learning models, deep learning frameworks, and large language models (LLMs). Model Evaluation Skills: Proven experience in evaluating AI models, including benchmarking, fine-tuning, and model assessment. Attention to Detail: Strong ability to identify linguistic nuances, model errors, and biases in AI model outputs. Data Management: Skilled in managing and curating large datasets, understanding data preprocessing and data cleaning for AI model training. Analytical Mindset: Ability to perform quantitative and qualitative assessments of AI model performance, including the development of evaluation metrics. Qualifications: Education: Bachelor’s or Master’s degree in Linguistics, Language, or similar experience in the previous jobs. Experience: 2-3 years of experience in linguistics, NLP, or AI model evaluation, with a focus on large-scale data curation.