MLOps Engineer

Charlotte, VT - USA

Monthly Salary: Not Disclosed

Posted on: 11 hours ago

Vacancies: 1 Vacancy

Job Summary

Predictive AI team seeking ML Ops Engineers to drive the full lifecycle of machine learning
solutions.

Key Responsibilities
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
Leverage AutoML tools (e.g. Vertex AI AutoML H2O Driverless AI) for low-code/no code model development documentation automation and rapid deployment

Qualifications
10 Years of professional experience in Software Engineering & 3 Years in AIML
Machine Learning Model Operations.
Strong proficiency in Java and 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.

Location: Bay Area

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Predictive AI team seeking ML Ops Engineers to drive the full lifecycle of machine learning solutions. Key Responsibilities Develop and maintain ML pipelines using tools like MLflow Kubeflow or Vertex AI. Automate model training testing deployment and monitoring in cloud environments (e...