Generative AI Engineer
2 weeks ago
Job descriptionRole : Generative AI EngineerLocation - BangaloreExperience - 6+ YearsNotice Period: Immediate joinerCore Responsibilities: Collaborate with cross-functional teams to translate complex AI concepts into practical business solutions. Design systems around open source, enterprise models like Llama, Gemini, GPT to solve innovative problems. Build robust evaluation pipelines to assess model performance, safety, and alignment with business objectives. Optimize model latency and performance for real-time applications and large-scale deployment Architect scalable ML infrastructure for training, inference, and model serving Fine-tune Large Language Models (LLMs) and other transformer-based architectures Ability to explain complex AI concepts to technical and non-technical stakeholdersWhat We're Looking ForExperience Requirements: 6+ years of overall data science or ML experience. 1.5+ years of hands-on experience with generative AI and large language models. Advanced degree in Computer Science, Machine Learning, or related field. Experience in taking ML/DL model to production.️ Technical Expertise: Python, C++ or any other high-level language. PyTorch and TensorFlow. Experience with Hugging Face Transformers, LangChain, LlamaIndex,Pydantic AI Deep Learning fundamentals: neural networks, backpropagation, optimization Generative AI frameworks: OpenAI API, Anthropic Claude, Google Gemini,local LLM deployment Model architectures: Transformers, attention mechanisms, encoder-decoder models Fine-tuning techniques: LoRA, QLoRA, full parameter fine-tuning, RLHF Design and implement comprehensive evaluation pipelines A/B testing for AI systems and statistical significance testing Latency optimization techniques: model quantization, pruning, distillation Experience with MLOps tools: MLflow, Weights & Biases, DVCTechnical skill: Python, C++, PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Pydantic AI, Deep Learning, Neural Networks, Optimization, OpenAI API, Claude, Gemini, LLM Deployment, Transformers, Encoder-Decoder, LoRA, QLoRA, RLHF, A/B Testing, Quantization, Pruning, Distillation, MLflow, Weights & Biases, DVC.
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