Build and operate MLOps and agentic infrastructure: manage model registries, continuous training loops, and A/B testing; deploy agents as scalable Kubernetes microservices; and create observability dashboards tracking token usage, latency, and agent reasoning.
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 strong DevOps/MLOps background and be adept at deploying scalable microservices and building observability dashboards.
Responsibilities:
- Manage model registries, continuous training loops, and A/B testing infrastructure.
- Deploy agents as scalable microservices on Kubernetes.
- Build observability dashboards to track token usage, latency, and agent reasoning paths.
Qualifications:
- Strong DevOps/MLOps background (Kubernetes, Docker, Terraform).
- Experience with MLflow, Weights & Biases, or LangSmith.
- Knowledge of building scalable microservice architectures.
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What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
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