AI/ML Architect

Job Summary

We are seeking an experienced AI/ML Architect to lead the design and development of scalable, real-time AI systems. You will work closely with product, data, and engineering teams to architect end-to-end solutions — from model development and deployment to system integration and production monitoring.

Key Responsibilities

• Design and architect AI/ML systems that are scalable, low-latency, and production-ready
• Lead development of real-time inference pipelines for use cases like voice, vision, or NLP
• Select and integrate appropriate tools, frameworks, and infrastructure (e.g., Kubernetes, Kafka, Tensor. Flow, Py. Torch, ONNX, Triton, VLLM etc.)
• Collaborate with data scientists and ML engineers to productionize models
• Ensure reliability, observability, and performance of deployed systems
• Conduct architecture reviews, POCs, and system optimizations
• Mentor engineers and help set best practices for ML lifecycle (MLOps) Requirements
• 6+ years of experience building and deploying ML systems in production
• Proven expertise in real-time, low-latency system design (e.g., streaming inference, event-driven pipelines)
• Strong understanding of scalable architectures — microservices, message queues, distributed training/inference
• Proficient in Python and popular ML/DL frameworks (scikit-learn, Tensor. Flow, Py. Torch)
• Hands-on experience with LLM inference optimization using frameworks like vLLM, TensorRT-LLM, and SGLang
• Familiarity with vector databases, embedding-based retrieval, and RAG pipelines
• Experience with containerized environments (Docker, Kubernetes) and managing multi-container applications
• Working knowledge of cloud platforms (AWS, GCP, or Azure) and CI/CD practices for ML workflows
• Exposure to edge deployments and model compression/optimization techniques
• Strong foundation in software engineering principles and system design Nice to Haves
• Experience in Linux (Ubuntu)
• Terminal/Bash Scripting