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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Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
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