Technical Expertise and Required Qualifications
- 5–8 years of experience in ML engineering, DevOps, or data platform engineering, with at least 2 years in MLOps or model operations.
- Proficiency in Python, particularly for automation, data processing, and ML model development.
- Solid experience with SQL and distributed query engines (e.g., Trino, Spark SQL).
- Deep expertise in Docker, Kubernetes, and cloud-native container orchestration tools (e.g., OCI Container Engine, EKS, GKE).
- Working knowledge of open-source data lakehouse frameworks and data versioning tools (e.g., Delta Lake, Apache Iceberg, DVC).
- Familiarity with model deployment strategies, including batch, real-time inference, and edge deployments.
- Experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins) and MLOps frameworks (Kubeflow, MLflow, Seldon Core).
- Competence in implementing monitoring and logging systems (e.g., Prometheus, ELK Stack, Datadog) for ML applications.
- Strong understanding of cloud platforms (OCI, AWS, GCP) and IaC tools (Terraform, CloudFormation).
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical discipline.
Preferred Qualifications
- Experience integrating AI workflows with Oracle Data Lakehouse, Databricks, or Snowflake.
- Hands-on experience with orchestration tools like Apache Airflow, Prefect, or Dagster.
- Exposure to real-time ML systems using Kafka or Oracle Stream Analytics.
- Understanding of vector databases (e.g., Oracle 23ai Vector Search).
- Knowledge of AI governance, including model explainability, auditability, and reproducibility frameworks.
Soft Skills
- Strong problem-solving skills and an automation-first mindset.
- Excellent cross-functional communication, especially when collaborating with data scientists, DevOps, and platform engineering teams.
- A collaborative and knowledge-sharing attitude, with good documentation habits.
- Passion for continuous learning, especially in the areas of AI/ML tooling, open-source platforms, and data engineering innovation.
Responsibilities
- Design, implement, and automate ML lifecycle workflows using tools like MLflow, Kubeflow, Airflow and OCI Data Science Pipelines.
- Build and maintain CI/CD pipelines for model training, validation, and deployment using GitHub Actions, Jenkins, or Argo Workflows.
- Collaborate with data engineers to deploy models within modern data lakehouse architectures (e.g., Apache Iceberg, Delta Lake, Apache Hudi).
- Integrate machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn into distributed environments like Apache Spark, Ray, or Dask.
- Operationalize model tracking, versioning, and drift detection using DVC, model registries, and ML metadata stores.
- Manage infrastructure as code (IaC) using tools like Terraform, Helm, or Ansible to support dynamic GPU/CPU training clusters.
- Configure real-time and batch data ingestion and feature transformation pipelines using Kafka, Goldengate and OCI Streaming.
- Collaborate with DevOps and platform teams to implement robust monitoring, observability, and alerting with tools like Prometheus, Grafana, and the ELK Stack.
- Support AI governance by enabling model explainability, audit logging, and compliance mechanisms aligned with enterprise data and security policies.
Qualifications
Career Level - IC3
About Us
As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity.We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all.Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs.We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States.Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
