Available for new projects · Remote worldwide

    MLOps Consultant

    A model is not finished when the notebook looks good. I help teams build the pipelines, deployment paths, monitoring, and evaluation workflows that keep machine learning systems reliable after they meet real users and changing data.

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    What I can help with

    • Reproducible training pipelines and experiment tracking
    • Batch or real-time model deployment
    • Model monitoring for drift, latency, quality, and cost
    • Evaluation harnesses and retraining workflows
    • Cloud-native MLOps on AWS, GCP, or existing infrastructure

    Why work with me

    Remote-first, worldwide

    Fully remote delivery with clients across the US, Europe, and Asia — async-friendly and outcome-focused.

    Timezone overlap

    Based in Islamabad (PKT), with working-hours overlap into both US and European mornings/evenings.

    Fixed-price clarity

    Scoped proposals with clear deliverables and timelines — no open-ended retainers required to start.

    Fast, senior delivery

    Direct work with one experienced engineer — no account managers, no hand-offs, working software each sprint.

    Relevant services

    ML Systems & MLOps

    Frequently asked questions

    Can you productionize a model our team already trained?
    Yes. I can take an existing notebook or model artifact and build the training pipeline, serving layer, monitoring, evaluation, and documentation around it.
    What should an MLOps engagement deliver?
    A good MLOps engagement should leave you with reproducible training, deployable model versions, monitoring dashboards or alerts, a retraining path, and clear ownership documentation.

    Let's talk about your project

    Tell me what you're working on and I'll come back with ideas, a scope, and next steps — usually within 24 hours. Free discovery call, no commitment.

    Start a project[email protected]