Lead Research Scientist - Generative AI

As a Generative AI Developer, your role will involve designing, building, and deploying solutions powered by Large Language Models (LLMs), multimodal AI, and prompt engineering. You will collaborate closely with product and engineering teams to integrate GenAI capabilities into real-world applications such as chatbots, copilots, content generation, and intelligent automation. Key Responsibilities: - AI/ML Development: - Fine-tune and optimize LLMs (GPT, LLaMA, Claude, etc.) for specific business use cases. - Build and deploy GenAI-powered applications like chatbots, copilots, summarization, Q&A systems, and generative content. - Experiment with multimodal AI involving text, image, audio, and video. - Prompt Engineering & Orchestration: - Design effective prompts and workflows to maximize model performance. - Work with frameworks like LangChain, LlamaIndex, and Haystack for retrieval-augmented generation (RAG). - Backend & Integration: - Develop APIs and services to integrate GenAI models into existing platforms. - Connect AI with structured and unstructured data sources. - Cloud & Deployment: - Deploy models on AWS, Azure, or GCP (SageMaker, Vertex AI, Azure OpenAI). - Implement scalable and cost-efficient inference pipelines. - MLOps & Performance: - Monitor AI models in production including latency, accuracy, and hallucination rates. - Implement continuous training, evaluation, and improvement workflows. Required Skills & Qualifications: - Strong programming skills in Python (Node.js/Java is a plus). - Hands-on experience with GenAI/LLMs (OpenAI, Anthropic, Hugging Face, Cohere, Stability AI). - Familiarity with LangChain, LlamaIndex, and RAG pipelines. - Knowledge of NLP, embeddings, vector databases (Pinecone, Weaviate, Milvus, FAISS). - Experience with cloud platforms (AWS, Azure, GCP) and deployment of ML models. - Understanding of prompt design, fine-tuning, and model evaluation. - Solid grasp of APIs, microservices, and REST/GraphQL integrations. Preferred: - Experience with multimodal models (text-to-image, speech-to-text, etc.). - Exposure to containerization and orchestration (Docker, Kubernetes). - Knowledge of data privacy, security, and compliance in AI systems. - Prior work in AI-driven SaaS products. In this role, you will have the opportunity to contribute to cutting-edge projects in the field of Generative AI. If you have experience deploying applications or AI models on cloud platforms, familiarity with AI/ML frameworks, and working with CDN platforms for scaling applications, we encourage you to apply for this full-time position.,