
Building Scalable AI Infrastructure
17 hours ago
About this role
Grow businesses with AI/ML solutions.
- Develop and deploy cutting-edge AI systems with a strong focus on LLMs, Retrieval-Augmented Generation (RAG), AI agents, and intelligent automation.
Work closely with cross-functional teams to translate business needs into AI solutions.
Key Responsibilities:AI & ML System Development- Design, develop, and optimize end-to-end ML models using LLMs, transformer architectures, and custom RAG frameworks.
- Fine-tune and evaluate generative and NLP models for business-specific applications such as conversational flows, auto-replies, and intelligent routing.
- Lead prompt engineering and build autonomous AI agents capable of executing multi-step reasoning.
- Architect and automate scalable training, validation, and deployment pipelines using tools like MLflow, SageMaker, or Vertex AI.
- Integrate ML models with APIs, databases, and production services ensuring performance, reliability, and traceability.
- Monitor model performance in real-time, and implement A/B testing, drift detection, and re-training pipelines.
- Work with structured, unstructured, and semi-structured data (text, embeddings, chat history).
- Build and manage vector databases and graph-based retrieval systems.
- Ensure high-quality data ingestion, feature pipelines, and scalable pre-processing workflows.
- Collaborate with product managers, software engineers, and stakeholders to align AI roadmaps with product goals.
- Mentor junior engineers and establish best practices in experimentation, reproducibility, and deployment.
- Stay updated on the latest in AI/ML, and drive innovation in applied use cases.
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