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    Sr. Machine Learning Engineer

    Remote

    Build and deploy production ML/LLM systems end-to-end — from data and evaluation to scalable inference and monitoring.

    Key responsibilities

    • Design and implement production ML services (batch + real-time) with clear interfaces and SLAs.
    • Build evaluation harnesses (offline + online), create baselines, and iterate with tight feedback loops.
    • Own model training/fine-tuning workflows and/or RAG pipelines with strong observability.
    • Partner with product and engineering to translate requirements into shipped systems.
    • Improve reliability, latency, and cost of inference in production.

    Ideal candidate

    • 5+ years building AI/ML or data-driven systems in production.
    • Strong Python engineering (packaging, testing, performance) and experience with ML tooling.
    • Experience with LLM integrations (prompting, tool use, RAG) and/or traditional ML pipelines.
    • Hands-on experience with cloud infrastructure (AWS/GCP/Azure) and containerization (Docker).
    • Comfortable owning systems end-to-end, including monitoring and incident response.

    Preferred

    • Experience with vector databases and retrieval evaluation.
    • Experience with distributed compute (Ray/Spark) and feature stores.
    • Experience with MLOps tooling (CI/CD for models, model registry, drift monitoring).