Generative AI Engineer

Full Description

Job description

We are seeking a highly skilled Senior Generative AI Engineer.

The ideal candidate will have 3+ years of experience in designing, optimizing, and deploying Large Language Models (LLMs) with expertise in fine-tuning, vector databases, GPU-based performance optimization, and AI-driven automation.

This role requires a deep understanding of cutting-edge AI models, cloud deployment strategies, and enterprise-scale AI solutions.

Key Responsibilities Advanced AI Model Development

• Architect and optimize LLM-based generative AI models such as LLaMA, GPT-4, and Falcon.

• Implement model compression techniques like LoRA, quantization, and PEFT for efficiency.

• Utilize GPU-accelerated frameworks (CUDA, TensorRT, PyTorch) for optimized training and inference.

NLP and AI Applications

• Develop NLP solutions for chatbots, summarization, semantic search, and contextual understanding.

• Implement intent recognition, entity extraction, and sentiment analysis.

Vector Database and AI Memory Systems

• Work with FAISS, Pinecone, Milvus, and ChromaDB for high-performance vector search.

• Develop pipelines for embedding generation and real-time AI applications.

GPU Optimization and Large-Scale AI Deployments

• Optimize LLM performance using TensorRT, ONNX Runtime, and multi-GPU parallelization.

• Enhance model efficiency, cost reduction, and scalability for production environments.

Cloud Deployment & AI Infrastructure

• Deploy AI models on AWS SageMaker, Azure AI, or Google AI Platform.

• ⁠Implement APIs, microservices, and end-to-end AI pipelines.

Research & Innovation

• Stay ahead of AI trends and emerging technologies, implementing LangChain, Auto-GPT, and DeepSpeed for AI orchestration.

• Contribute to LLM lifecycle management, reinforcement learning, and adaptive AI frameworks.

Required Skills & Qualifications

• Bachelor’s/Master’s degree in Computer Science, AI, or Machine Learning.

• 3+ years of experience in LLM development, optimization, and AI deployment.

• Strong expertise in Python, PyTorch, TensorFlow, and Hugging Face Transformers.

• Experience with Meta’s LLaMA, GPT-4, Falcon, or similar architectures.

• Hands-on experience with vector databases (FAISS, Pinecone, Milvus).

Deep understanding of GPU-based AI development (CUDA, TensorRT, ONNX Runtime).

• Experience with cloud-based AI deployments (AWS, Azure, GCP).

Preferred Skills

• Experience with LangChain, Auto-GPT, and DeepSpeed for AI pipeline orchestration.

• Knowledge of MLOps and LLM lifecycle management.

• Familiarity with Weights & Biases (WandB) for AI experimentation tracking.

• ⁠Exposure to reinforcement learning and agent-based AI systems.