Sr MLop engineer
Share
Job Location:
San Leandro, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
10-09-2025
Vacancies:
1 Vacancy
Job Summary
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.
Key Skills
- ASP.NET
- Health Education
- Fashion Designing
- Fiber
- Investigation
