Generative AI Engineer

About the Role

Generative AI Engineer

Key Responsibilities

• Model Development & Fine-Tuning

• Build, fine-tune, and optimize LLMs, multimodal models, and generative models (e.g., GPT-based, Llama, Stable Diffusion).
• Develop custom training pipelines using frameworks like PyTorch, TensorFlow, or JAX.
• Perform prompt engineering, prompt optimization, and model evaluation.

• Solution Architecture

• Design and implement scalable GenAI-driven systems (chatbots, copilots, RAG systems, content generation engines, etc.).
• Integrate models with enterprise systems via APIs, microservices, or cloud platforms.

• Data Engineering & MLOps

• Prepare and curate datasets for training/finetuning using synthetic data generation, labeling, and cleansing.
• Build end-to-end MLOps pipelines for continuous training, monitoring, and model deployment.
• Optimize model performance for latency, accuracy, and cost.

• Research & Innovation

• Stay updated with the latest advancements in LLMs, transformers, generative modeling, and retrieval systems.
• Experiment with new architectures, embeddings, vector databases, and inference optimization techniques (quantization, distillation, LoRA).

• Collaboration

• Work cross-functionally with product, engineering, and UX teams to define and deliver GenAI-powered features.
• Communicate technical concepts clearly to stakeholders.

Required Skills & Qualifications

• Python Programming, Traditional ML, GenAI, Scaled AI, GitLab, Agentic framework, MCP, AWS Sagemaker
• Building end-to-end Gen AI-based Authoring pipelines and agents

Why Join Us

• Work on cutting-edge GenAI projects that impact millions of users.
• Collaborate with a highly skilled AI team and industry experts.
• Competitive compensation, learning opportunities, and an innovation-driven culture.
• Opportunity to shape the future of AI within our organization.