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Lead Research Scientist
2 weeks ago
We are seeking a Generative AI Developer to design, build, and deploy solutions powered by Large Language Models (LLMs), multimodal AI, and prompt engineering. You will work closely with product and engineering teams to integrate GenAI capabilities into real-world applications — from chatbots and copilots to 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 (chatbots, copilots, summarization, Q&A systems, generative content).
- Experiment with multimodal AI (text, image, audio, video).
- Prompt Engineering & Orchestration
- Design effective prompts and workflows to maximize model performance.
- Work with frameworks like LangChain, LlamaIndex, Haystack for retrieval-augmented generation (RAG).
- Backend & Integration
- Develop APIs and services to integrate GenAI models into existing platforms.
- Connect AI with structured/unstructured data sources.
- Cloud & Deployment
- Deploy models on AWS, Azure, or GCP (SageMaker, Vertex AI, Azure OpenAI).
- Implement scalable, cost-efficient inference pipelines.
- MLOps & Performance
- Monitor AI models in production (latency, accuracy, hallucination rates).
- Implement continuous training, evaluation, and improvement workflows.
Required Skills & Qualifications
- Strong programming skills in Python is a plus).
- Hands-on experience with GenAI/LLMs (OpenAI, Anthropic, Hugging Face, Cohere, Stability AI).
- Familiarity with LangChain, LlamaIndex, 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 & orchestration (Docker, Kubernetes).
- Knowledge of data privacy, security, and compliance in AI systems.
- Prior work in AI-driven SaaS products.
Job Type: Full-time
Pay: ₹510, ₹1,591,431.67 per year
Application Question(s):
- Which cloud platforms have you deployed applications or AI models on?
- How many years of experience do you have working with AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, LangChain)
- Have you worked with CDN platforms such as Cloudflare, Akamai, or AWS CloudFront for scaling applications?
Work Location: In person