AI/ML Architect

Job Summary

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)

Nice to Haves