AI & Machine Learning

I bring AI systems to production - from prototype to a model people actually rely on. Last 3 years: building, training, and shipping models in fintech and consumer products.

  • What I do

    • Production ML pipelines (training, eval, deploy, monitor)
    • LLM and agent systems: RAG, tool use, evals, guardrails
    • Computer vision and on-device / in-browser inference
    • Real-time scoring: fraud, risk, recommendations

  • Stack

    • PyTorch, Transformers, Vertex AI, MLflow
    • Kafka, Spark, BigQuery
    • Kubernetes, Docker, GitHub Actions

  • What you get

    • A model in production, not a notebook
    • Evals you trust and dashboards you read
    • A team that can keep iterating after I leave
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