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    Machine Learning Engineer - San Antonio, United States - Brooksource

    Brooksource
    Brooksource San Antonio, United States

    2 weeks ago

    Default job background
    Description
    *Machine Learning (MLOps) Engineer


    • 6+ Month Contract-to-Hire
    *San Antonio, TX (Hybrid)

    Our client is looking for highly motivated Staff Engineer. Bring your passion and dedication, and there's no telling what you could accomplish.

    If working in a fast-paced environment that challenges your technical abilities on a day-to-day basis is exciting to you, you have found your new home.

    *Responsibilities
    • Assembling large, complex sets of data that meet non-functional and functional business requirements.
    • Has experience leading a team through End to End development – Data Extraction, Data Engineering, Feature Engineering, Testing and training, Model development and deployment.
    • Has vast experience and hands-on in building Enterprise level applications.
    • Mentoring team of Engineers with Industry's best practices.
    • Identifying, designing, and implementing internal process improvements including redesigning infrastructure for greater scalability, optimizing data delivery, and automating manual processes.
    • An expert at building high quality, scalable and resilient distributed systems.
    • Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using GCP technologies.
    • Improving internal processes through machine learning (ML), including increasing velocity in
    • ML model building, reducing time to production, and providing solutions for production-level
    • ML challenges such as versioning, lineage, and reproducibility.
    • Working with stakeholders including product teams to support their Technical Product needs while assisting the data- related technical issues.
    • Building Analytics and solutions to enable business users in making time-sensitive and critical decisions.
    • Has researched and implemented various models including but not limited to DNN, xgBoost,
    • Biq Query Arima, Linear Regression, Decision tree
    • Has increased accuracy of model and identified and fixed Data drifts and model drifts.
    • Build predictive models and machine-learning algorithms using distributed computing for Data Engineering and Training.
    • Expertise designing and implementing data pipelines using modern data engineering approach and tools: PySpark, Scala Scala, Dataproc, Databricks etc.
    • Focus on analyzing and interpreting data to find insights, trends and patterns.
    • Create analytics solutions for businesses by combining various tools, applied statistics, and machine learning
    • Lead discussions and initiatives and assess the feasibility of AI/ML solutions for business processes and outcomes
    • We are looking for someone with at least four 10+ years of professional experience as a ML Engineer/Data science/Data Engineer, a bachelor's degree in CS/EE and are self-driven, highly motivated and able to learn quickly.
    *Experience
    • Python, Scala
    • Spark, Ray
    • Kubernetes, Docker, Dataform and ML pipelines
    • Big Query
    • Databricks, Dataproc
    • Vertex AI, Bigquery ML, TensonFlow
    • Datadog, Relic


    _Eight Eleven Group provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state, and local laws.

    _

    #tech


    Job Type:
    Contract


    Pay:
    From $85.00 per hour

    Expected hours: 40 per week


    Benefits:

    • Dental insurance
    • Health insurance
    • Vision insurance

    Schedule:

    • Monday to Friday

    Ability to Commute:

    • San Antonio, TX (Required)

    Ability to Relocate:

    • San Antonio, TX: Relocate before starting work (Required)

    Work Location:
    In person

    #J-18808-Ljbffr
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