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, TensorFlow, PyTorch, 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, TensorFlow, PyTorch)

· 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