Sr. AI/ML Engineer

Architect multi-agent systems and autonomous workflows (Google AI SDK, LangGraph, LangChain); build cloud-native deployments with Terraform/Kubernetes/Docker; apply rigorous statistical evaluation (uncertainty, calibration, LoRA/QLoRA); develop custom predictive/deep-learning models (PyTorch, scikit-learn); champion MLOps with Kubeflow/Vertex AI Pipelines; and work directly with clients. Requires 7+ years technical experience (3+ in ML/AI, 1 in consulting), agentic-loop/tool-use experience, deep Python AI stack (NumPy/Pandas/PyTorch + LLMOps tools), and strong probabilistic/Bayesian statistics. GCP Professional ML Engineer cert expected.