MLops Engineer

  • San Leandro, CA
  • Posted 13 hours ago | Updated 13 hours ago

Overview

On Site
$65 - $70
Contract - W2
Contract - 1 month(s)
No Travel Required

Skills

Predictive Modeling
Structured
AutoML
Vertex AI AutoML
H2O Driverless AI

Job Details

Job Description:

Pay Range: $65hr - $70hr

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., Google Cloud Platform, 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.
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