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    Machine Learning Engineer - Cincinnati, United States - Golden Technology

    Golden Technology
    Golden Technology Cincinnati, United States

    1 week ago

    Default job background
    Retail
    Description

    Looking for only United States citizens.

    Job Description-

    Technical Skills and Expertise


    • Machine Learning Proficiency: Strong understanding of machine learning algorithms and principles, especially those relevant to anomaly detection, such as supervised and unsupervised learning, clustering, and neural networks.


    • Data Handling: Expertise in managing, processing, and analyzing large datasets. Familiarity with data cleaning, data transformation, and feature engineering is crucial.


    • Programming Skills: Proficiency in programming languages commonly used in machine learning such as Python.


    • Model Development and Evaluation: Ability to develop robust ML models and evaluate their performance through metrics specific to anomaly detection.


    • System Integration: Skills to integrate ML models into existing systems for seamless data flow and model deployment including Azure big data and analytics experience.

    Problem-Solving Skills


    • Analytical Thinking: Ability to analyze complex data and identify patterns or inconsistencies that may indicate problems.


    • Creative Problem Solving: Capacity to devise innovative solutions that improve detection and prediction of anomalies.


    • Attention to Detail: Precision in model tuning and the interpretation of data to ensure high accuracy and reliability of outputs.

    Communication and Collaboration


    • Clear Communication: Ability to explain complex ML concepts and findings to non-technical stakeholders.


    • Collaborative Spirit: Willingness to work closely with IT teams, data scientists, and other departments to ensure models align with broader business objectives.

    Key Responsibilities

    Ensure adherence to architecture standards and roadmaps.

    Implement overall infrastructure / middleware components per project with infrastructure teams, ensuring that overall solution is designed to meet SLA (performance and up-time), DR, and scalability needs required by the solution.

    Design and successfully implement overall infrastructure / middleware components per project with infrastructure teams, ensuring that overall solution is designed to meet SLA (performance and up-time), DR, and scalability needs required by the solution.

    Ensure that post-production operational processes / deliverables are well designed and implemented prior to the project moving into the solution support phase.

    Define and create operational procedures, processes, and scripts.

    Follow appropriate change/release management practices.

    Support and maintain infrastructure solutions utilizing required tools and technologies. Provide off-hours support (24 x 7) as required

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