Lead AI Engineer – LLM
5 days ago
About Senzcraft:Founded by IIM Bangalore and IEST Shibpur Alumni, Senzcraft is a hyper-automation company. Senzcraft vision is to Radically Simplify Today's Work. And Design Business Process For The Future. Using intelligent process automation technologies.We have a suite of SaaS products and services, partnering with automation product companies.Please visit our website - https://www.senzcraft.com for more detailsOur AI Operations SaaS platform – https://MagicOps.aiSenzcraft on linkedin -> https://www.linkedin.com/company/senzcraftSenzcraft is awarded by Analytics India Magazine in it’s report “State of AI in India” as a “Niche AI startup”. Senzcraft is also recognized by NY based SSON as a top hyper-automation solutions provider.About the role (Lead AI Engineer - LLM):Location: Bangalore – HybridExperience: We have multiple roles open (6-12 years)Employment Type: Full-timeJob Description:We are looking for a Lead AI Engineer with deep expertise in NLP, Large Language Models (LLMs), and Prompt Engineering to drive end-to-end AI-based solutions — from experimentation to production.The ideal candidate will have hands-on experience in fine-tuning, optimizing, and prompt-engineering transformer-based models (e.g., GPT, BERT, T5) for real-world business applications.Key Responsibilities- Fine-tune, adapt, and optimize LLMs and NLP models (GPT, BERT, T5, etc.) for supply chain and logistics–specific tasks such as demand forecasting, shipment tracking insights, and document understanding. - Design, engineer, and optimize prompts to improve model accuracy, contextual understanding, and task-specific performance. - Build and deploy scalable NLP solutions (e.g., summarization, chatbots, semantic search) tailored for supply chain applications. - Lead experimentation, model evaluation, and inference optimization for production environments. - Collaborate with data engineering and MLOps teams for model deployment, monitoring, and lifecycle management. - Mentor junior data scientists and ensure best practices in model development, fine-tuning workflows, and prompt design strategies.Mandatory Skills- Proven experience in fine-tuning, optimizing, and prompt-engineering large transformer-based models for production. - Strong proficiency in Python, PyTorch/TensorFlow, and Hugging Face Transformers. - Deep understanding of NLP techniques — tokenization, embeddings, attention mechanisms, and contextual modeling. - Familiarity with MLOps tools (MLflow, Docker, Kubernetes) and cloud ML platforms (AWS, GCP, Azure).Good to Have- Experience with RAG (Retrieval-Augmented Generation) and vector databases (FAISS, Pinecone). - Exposure to multimodal models and open-source LLM contributions. - Hands-on experience in prompt evaluation frameworks and prompt optimization pipelines.Education- Master’s or Bachelors in Computer Science, Data Science, or a related field.
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