3 - 6 years
5 - 8 Lacs
Posted:6 hours ago|
Platform:
Work from Office
Full Time
Experience: 3 to 6 years CTC 10 LPA Location: Whitefield, Bangalore We are seeking a highly skilled AI Engineer with deep expertise in Large Language Models (LLMs) and Natural Language Processing (NLP) to design, fine-tune, and deploy cutting-edge AI-driven text applications. The ideal candidate will have hands-on experience in prompt engineering, transformer-based model fine-tuning, and ML Ops practices for scalable deployment. Key Responsibilities: Collaborate with Daimler s business units and enabling areas to identify and support high-impact AI use cases. Design and develop LLM-based applications using models such as GPT, LLaMA, BERT, etc. Fine-tune and optimize LLMs for tasks including sentiment analysis, summarization, translation, and conversational AI. Work with embeddings, tokenization, and vector databases (e.g., FAISS, Pinecone) for semantic search and retrieval. Integrate AI models into production systems in collaboration with product and engineering teams. Apply ML Ops best practices for model lifecycle management, including versioning, monitoring, and CI/CD pipelines. Ensure compliance with ethical AI standards, data privacy regulations, and GDPR. Communicate findings and recommendations effectively to executive stakeholders through high-quality deliverables and presentations. Required Skills & Qualifications: Proven experience with NLP libraries and frameworks such as Hugging Face Transformers, spaCy, NLTK, and OpenAI API. Solid understanding of ML Ops tools and practices for managing AI workflows in production. Strong understanding of transformer architectures and experience fine-tuning LLMs. Proficiency with vector databases and semantic search technologies. Experience with model optimization techniques such as quantization and distillation. Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Familiarity with data governance, model interpretability, and responsible AI frameworks. Demonstrated success in deploying at least one LLM-based application to production. Strong problem-solving skills, attention to detail, and ability to work in cross-functional teams.
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