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    Machine Learning Ops Manager - Irving, TX, United States - Exeter Finance LLC

    Exeter Finance LLC
    Exeter Finance LLC Irving, TX, United States

    2 days ago

    Default job background
    Full time
    Description
    At Exeter Finance, we are committed to helping customers find the right financing for their next vehicle purchase.

    By building strong relationships with our customers and network of dealer partners we are able to give options that make sense, getting customers behind the wheel of their car.

    Every team member is integral to our success.

    Whether you're at a servicing center helping customers with their loans, in the field building relationships with dealers, or supporting the company from its corporate offices, you'll enjoy a nurturing, invigorating and positive work environment.

    Our vision is to be a premier finance company and lender of choice known for its People, Performance and Service.

    Job Description

    We are looking for an experienced and passionate MLOps Lead Engineer to join our team and lead the deployment and management of our machine learning solutions for a non-prime lender.

    As an MLOps Lead Engineer, you will be leading a team that implements and maintains end-to-end machine learning pipelines using Azure ML and other Azure services.

    You will work closely with data scientists, software engineers, and business stakeholders to ensure that our predictive models are implemented in a reliable, scalable, and efficient manner.

    You will also automate model testing, deployment, and monitoring using CI/CD best practices and MLOps principles.

    You will use your expertise in Python and Azure platform to enhance speed and efficiency of model computations using various advanced coding techniques.

    You will troubleshoot and resolve any issues related to data quality, model computation accuracy, and system reliability. You will also establish and enforce standards and best practices for machine learning operations. You will collaborate with cross-functional teams to understand business requirements and provide technical guidance and support. You will also research and evaluate new technologies and trends in MLOps.

    ESSENTIAL FUNCTIONS
    Implement, and maintain end-to-end machine learning pipelines using Azure ML and other Azure services
    Automate model testing, deployment, and monitoring using CI/CD best practices and MLOps principles
    Troubleshoot and resolve any issues related to data quality, model accuracy, and system reliability
    Establish and enforce standards and best practices for machine learning operations
    Collaborate with cross-functional teams to understand business requirements and provide technical guidance and support
    Research and evaluate new technologies and trends in MLOps
    Other duties as assigned.

    EDUCATION AND EXPERIENCE

    • Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
    • 5+ years of experience in deploying machine learning solutions using Azure
    • Proficient in Python, and familiar with common machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn.
    • Proficient in SQL. Experience with Microsoft SQL Server and Azure Datawarehouse strongly preferred.
    • Experience with DevOps tools and methodologies such as Git, Jenkins, Docker, Kubernetes
    • Experience with data engineering and data visualization tools such as Spark, Databricks, Power BI
    • Strong knowledge of machine learning concepts and techniques such as supervised and unsupervised learning, regression, classification, clustering
    • Excellent written and oral communication skills with good interpersonal skills.
    • Ability to work independently and lead a team of engineers.
    • Ability to problem-solve and multi-task on different projects of varied nature.
    #LI-Remote
    Exeter Finance LLC is an Equal Opportunity Employer.
    Individual compensation packages are based on various factors unique to each candidate including
    skill set, experience, qualifications and other job-related reasons.
    109,400.00 USD-$150,350.00
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