Generative AI Engineer

Job description

Role : Generative AI Engineer

Location - Bangalore

Experience - 6+ Years

Notice Period : Immediate joiner

Core 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 stakeholders

What We're Looking For

Experience 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, DVC

Technical 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.