ML Ops Engineer

TechDigital
  • San Leandro, CA
    12 days ago

    Job Description

    ML Ops Engineer to drive the full lifecycle of machine learning solutions—from data exploration and model development to scalable deployment and monitoring. This role bridges the gap between data science model development and production-grade ML Ops Engineering.

    Key Responsibilities
    • Develop predictive models using structured/unstructured data across 10+ business lines, driving fraud reduction, operational efficiency, and customer insights.
    • Leverage AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment
    • Develop and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.
    • Automate model training, testing, deployment, and monitoring in cloud environments (e.g., GCP, AWS, Azure).
    • Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and retraining.
    • Monitor model performance using observability tools and ensure compliance with model governance frameworks (MRM, documentation, explainability)
    • Collaborate with engineering teams to provision containerized environments and support model scoring via low-latency APIs
    Qualifications
    • Strong proficiency in Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
    • Experience with cloud platforms and containerization (Docker, Kubernetes).
    • Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks.
    • Solid understanding of software engineering principles and DevOps practices.
    • Ability to communicate complex technical concepts to non-technical stakeholders.

    Numbers & Facts

    LocationSan Leandro, CA
    IndustryOther/Not Classified
    Company Size100 to 499 employees

    Skills

    • Amazon Web Services (AWS)unmatched
    • Application Programming Interface (API)unmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Cloud Computingunmatched
    • Communication Skillsunmatched
    • Continuous Deployment/Deliveryunmatched
    • Continuous Integrationunmatched
    • Customer/Client Researchunmatched
    • Data Modelingunmatched
    • Data Scienceunmatched
    • DevOpsunmatched
    • Dockerunmatched
    • Documentationunmatched
    • Documentation Modelsunmatched
    • Environmental Monitoringunmatched
    • GCP (Good Clinical Practices)unmatched
    • Machine Learningunmatched
    • Maintain Complianceunmatched
    • Microsoft Windows Azureunmatched
    • Performance Analysisunmatched
    • Performance Modelingunmatched
    • Predictive Modelingunmatched
    • Python Programming/Scripting Languageunmatched
    • SQL (Structured Query Language)unmatched
    • Scalable System Developmentunmatched
    • Software Engineeringunmatched
    • Structured Dataunmatched
    • Unstructured Dataunmatched

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