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TechSci Research - Lead Data Scientist - LLM Models Job Opening In India, India – Now Hiring TechSci Research


Job description

<p><p><b>About the Role :</b></p><br/><p>The design and development of a cutting-edge application powered by large language models (LLMs).</p><br/><p>This tool will provide market analysis and generate high-quality, data-driven periodic insights.</p><br/><p>You will play a critical role in building a scalable and intelligent system that integrates structured data, NLP capabilities, and domain-specific knowledge to produce analyst-grade content.</p><br/><p><b>Key Responsibilities :</b></p><br/><p>- Design and develop LLM-based systems for automated market analysis.</p><br/><p>- Build data pipelines to ingest, clean, and structure data from multiple sources (e.g., market feeds, news articles, technical reports, internal datasets).</p><br/><p>- Fine-tune or prompt-engineer LLMs (e.g., GPT-4.5, Llama, Mistral) to generate concise, insightful reports.</p><br/><p>- Collaborate closely with domain experts to integrate industry-specific context and validation into model outputs.</p><br/><p>- Implement robust evaluation metrics and monitoring systems to ensure quality, relevance, and accuracy of generated insights.</p><br/><p>- Develop and maintain APIs and/or user interfaces to enable analysts or clients to interact with the LLM system.</p><br/><p>- Stay up to date with advancements in the GenAI ecosystem and recommend relevant improvements or integrations.</p><br/><p>- Participate in code reviews, experimentation pipelines, and collaborative research Required :</b></p><br/><p>- Strong fundamentals in machine learning, deep learning, and natural language processing (NLP).</p><br/><p>- Proficiency in Python, with hands-on experience using libraries such as NumPy, Pandas, and Matplotlib/Seaborn for data analysis and visualization.</p><br/><p>- Experience developing applications using LLMs (both closedand open-source models).</p><br/><p>- Familiarity with frameworks like Hugging Face Transformers, LangChain, LlamaIndex, etc.</p><br/><p>- Experience building ML models (e.g., Random Forest, XGBoost, LightGBM, SVMs), along with familiarity in training and validating models.</p><br/><p>- Practical understanding of deep learning frameworks: TensorFlow or PyTorch.</p><br/><p>- Knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), and LLM evaluation strategies.</p><br/><p>- Experience working with REST APIs, data ingestion pipelines, and automation workflows.</p><br/><p>- Strong analytical thinking, problem-solving skills, and the ability to convert complex technical work into business-relevant insights.</p><br/><p><b>Preferred :</b></p><br/><p>- Familiarity with the chemical or energy industry, or prior experience in market research/analyst workflows.</p><br/><p>- Exposure to frameworks such as OpenAI Agentic SDK, CrewAI, AutoGen, SmolAgent, etc.</p><br/><p>- Experience deploying ML/LLM solutions to production environments (Docker, CI/CD).</p><br/><p>- Hands-on experience with vector databases such as FAISS, Weaviate, Pinecone, or ChromaDB.</p><br/><p>- Experience with dashboarding tools and visualization libraries (e.g., Streamlit, Plotly, Dash, or Tableau).</p><br/><p>- Exposure to cloud platforms (AWS, GCP, or Azure), including usage of GPU instances and model hosting services.</p><br/></p> (ref:hirist.tech)

Required Skill Profession

Mathematical Science Occupations


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