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 Were 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.