We are seeking a skilled MLOps & Agentic Platform Engineer. This role involves managing model registries, developing continuous training loops, and implementing A/B testing infrastructure. The ideal candidate will have a robust Dev Ops/MLOps background and be adept at deploying scalable microservices and building observability dashboards.
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Responsibilities:
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Manage model registries, continuous training loops, and A/B testing infrastructure.
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Deploy agents as scalable microservices on Kubernetes.
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Build observability dashboards to track token usage, latency, and agent reasoning paths.
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Qualifications:
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Robust Dev Ops/MLOps background (Kubernetes, Docker, Terraform).
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Experience with MLflow, Weights & Biases, or Lang Smith.
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Knowledge of building scalable microservice architectures.