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

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  Design and architect AI/ML systems that are scalable, low-latency, and production-ready
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  Lead development of real-time inference pipelines for use cases like voice, vision, or NLP
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  Select and integrate appropriate tools, frameworks, and infrastructure (e.g., Kubernetes, Kafka, TensorFlow, PyTorch, ONNX, Triton, VLLM etc.)
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  Collaborate with data scientists and ML engineers to productionize models
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  Ensure reliability, observability, and performance of deployed systems
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  Conduct architecture reviews, POCs, and system optimizations
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  Mentor engineers and help set best practices for ML lifecycle (MLOps)

Requirements

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  6+ years of experience building and deploying ML systems in production
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  Proven expertise in real-time, low-latency system design (e.g., streaming inference, event-driven pipelines)
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  Strong understanding of scalable architectures — microservices, message queues, distributed training/inference
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  Proficient in Python and popular ML/DL frameworks (scikit-learn, TensorFlow, PyTorch)
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  Hands-on experience with LLM inference optimization using frameworks like vLLM, TensorRT-LLM, and SGLang
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  Familiarity with vector databases, embedding-based retrieval, and RAG pipelines
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  Experience with containerized environments (Docker, Kubernetes) and managing multi-container applications
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  Working knowledge of cloud platforms (AWS, GCP, or Azure) and CI/CD practices for ML workflows
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  Exposure to edge deployments and model compression/optimization techniques
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  Strong foundation in software engineering principles and system design

Nice to Haves

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  Experience in Linux (Ubuntu)
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  Terminal/Bash Scripting