2 months ago
Responsibilities
- Implement and productionize machine learning models with minimal guidance.
- Automate ML workflows from data extraction, transformation, and loading through model deployment and monitoring.
- Scale, clean, and maintain models to meet production quality standards.
- Monitor deployed model performance and interpret metrics for technical and non-technical stakeholders.
- Identify and help mitigate data quality, bias, fairness, security, and privacy issues.
- Integrate ML models into new and existing systems with data scientists and software developers.
- Troubleshoot ML infrastructure and workflows and provide debugging support.
- Develop and maintain internal tools, platforms, environments, and services.
- Write efficient, maintainable code and follow version control, code review, and continuous integration practices.
- Maintain documentation for experimentation, data collection, analysis, and model building.
- Collaborate with cross-functional stakeholders and independently manage work, timelines, and deliverables.
Requirements
- At least 8 years of relevant experience without a degree, or a bachelor's degree plus 4 years of relevant experience, or a master's degree plus 2 years of relevant experience.
- Relevant fields include data science, machine learning, software development, computer science, computer engineering, mathematics, physics, or a related field.
- Demonstrated cloud computing knowledge, including deploying, managing, and securing cloud environments and applications.
- Proficiency writing maintainable code in high-level programming languages and using major programming languages for software solutions.
- Demonstrated ability to conduct in-depth code reviews and apply quality assurance practices.
- Experience with predictive analytics and machine learning frameworks for real-world business scenarios.
- Troubleshooting experience across technical domains and knowledge of data security, privacy regulations, and security protocols.
- Preferred experience with automation, CI/CD and DevOps practices, generative AI and prompt engineering, and product performance analysis.
- A doctorate in a relevant field is also listed as a preferred qualification.
Benefits
- Competitive benefits including flexible medical, life insurance, and retirement options.
- Volunteer programs supporting employee community involvement.
- Accessibility assistance and workplace accommodations are available.
- Equal employment opportunity protections are provided.
Tech Stack
Categories
About Oracle
Oracle builds database technology, enterprise applications, and Oracle Cloud Infrastructure for companies and governments. Its business spans cloud subscriptions, software licenses, and support services across ERP, HCM, CX, and industry suites, plus NetSuite. Founded in 1977 and headquartered in Austin, Texas, Oracle is a public company traded on the NYSE and serves global customers migrating and running critical workloads in its cloud.