LLM/Generative AI Engineer

2 weeks ago

Gurgaon, Haryana, India Talent Integrators Full time

Role Overview :

We are seeking a highly motivated LLM Engineer with hands-on expertise in Large Language Models (LLMs) and Generative AI technologies. The ideal candidate will have experience in building end-to-end AI solutions, including RAG pipelines, vector databases, fine-tuning LLMs, and deploying scalable AI-powered applications. In this role, you will collaborate with cross-functional teams (data scientists, ML engineers, product managers) to design and deliver innovative AI systems that solve real-world business problems.

This is an exciting opportunity to work on state-of-the-art Generative AI models, influence technical strategy, and contribute to shaping the future of AI-driven solutions within the organization.

Key Responsibilities :

LLM Development & Deployment :

- Design, build, and deploy Generative AI applications leveraging models like GPT, LLaMA, Falcon, and other cutting-edge LLMs.

- Fine-tune and adapt pre-trained LLMs for domain-specific use cases.

RAG Pipelines & Vector Databases :

- Develop Retrieval-Augmented Generation (RAG) pipelines for intelligent and contextual responses.

- Implement vector search solutions using ChromaDB, Pinecone, Weaviate, LanceDB, or FAISS.

Prompt Engineering & Optimization :

- Design effective prompt engineering strategies for reliable model outputs.

- Implement embeddings, semantic search, and context optimization to improve accuracy and relevance.

AI Application Development :

- Work with LangChain, Hugging Face Transformers, and related frameworks for application development.

- Ensure AI solutions are scalable, efficient, and & Best Practices :

- Work closely with data science, product, and engineering teams to deliver impactful solutions.

- Stay updated with the latest research in NLP, LLMs, and Generative AI and adopt best practices.

Required Skills & Qualifications :

- Programming : Strong proficiency in Python with experience in ML/AI libraries.

- LLM Experience : Minimum 2+ years hands-on with LLMs & Generative AI.

- Frameworks & Tools : Practical knowledge of LangChain, Hugging Face Transformers, BERT, GPT models.

- Vector Databases : Expertise in ChromaDB, Pinecone, LanceDB, Weaviate, or FAISS.

- RAG Pipelines : Proven track record of building, optimizing, and deploying RAG solutions.

- Deep Learning & NLP : Strong understanding of Neural Networks, NLP techniques, and embeddings.

- Deployment : Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus.

Preferred Skills (Good to Have) :

- Experience with MLOps workflows and deployment of AI models in production.

- Knowledge of LLMOps frameworks for monitoring and managing LLM-powered applications.

- Hands-on experience with APIs & microservices architecture.

- Understanding of responsible AI practices (bias, fairness, interpretability).

(ref:hirist.tech)

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