Principal Machine Learning Engineer
Job Location:
Nashville, IN - USA
Yearly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
Implements machine learning (ML) models for production. Ensures the readiness of machine learning models for deployment in production. Automates machine learning workflows. Creates infrastructure and frameworks to monitor the performance of machine learning models in deployment. Evaluates potential data quality security and/or privacy issues and their impacts on modeling. Provides troubleshooting and debugging support. Addresses issues in machine learning infrastructure and workflows. Collaborates with stakeholders to integrate machine learning models into new or extant systems. Develops maintains and refines tools platforms and services for internal use. Develops efficient bug-free code from scratch. Maintains familiarity with current developments in the machine learning field and integrates knowledge into model development.
Responsibilities
KeyResponsibilities
MachineLearning and Data Modeling Model Productionization:
Utilizesmachine learning (ML) and software development knowledge to implement ML modelsfor production.
Engagesin transforming machine learning prototypes into production-ready models.
Collaborateswith multiple stakeholders such as Development Leads Product ManagementOperations and Release Management to make adopt and communicate technicaldecisions and shape the development and delivery of software.
ModelDevelopment and Deployment Model Deployment:
EnsuresML model readiness for deployment by scaling models cleaning model code andensuring production quality standards are met.
Automatesmachine learning workflows from data extraction transformation and loading(ETL) to model deployment and monitoring to establish the continuousintegration and continuous delivery of machine learning solutions.
ModelDevelopment and Deployment Model Performance:
Createsinfrastructure and frameworks to monitor the performance and alignment withdesign criteria of trained models and/or systems.
Proactivelymonitors the performance of deployed models and troubleshoots independently orin collaboration with Data Science.
Developsnovel metrics that provide analytical insights to non-technical stakeholders onhow well machine learning models are operating.
ModelDevelopment and Deployment Data Quality:
Evaluatespotential issues related to data quality (e.g. bias fairness) data securityand data privacy and minimizes their impacts on data analyses and modeling.
Engagesin tasks such as data cleaning preprocessing and feature identification toprepare for and enable model training.
InternalCollaborations and Impacts Model Integration and Operation:
Collaborateswith multiple stakeholders (e.g. data scientists software developers) tointegrate ML models into new or existing systems.
Maintainsthe partnership between model development and operations ensuring smoothdeployment and continuous improvement of ML models.
Understandsoperational considerations of model deployment (e.g. performance scalabilitystability maintenance).
Providesexpert troubleshooting and debugging support addresses issues in machinelearning infrastructure and workflow and creates robust solutions to preventfuture problems.
InternalCollaborations and Impacts Tool Development:
Developsmaintains and refines tools platforms environments and services forinternal use.
InternalCollaborations and Impacts Coding and Documentation:
Developsefficient bug-free medium-complexity code from scratch and properlymaintains and organizes the existing codebase.
Implementsbest practices for version control code review and code delivery/deployment.
Buildsand maintains professional documentation for technical processes(experimentation data collection and analyses model building).
Testsand reviews code for bugs.
MachineLearning Expertise:
Maintainsfamiliarity with current developments in the machine learning field andintegrates knowledge into model development.
Maintainsfamiliarity with the usage and development of third-party machine learningframeworks packages and libraries (e.g. PyTorch TensorFlow Keras) tocontinuously evaluate their performance and scalability and integrate theminto production environments.
CoreResponsibilities
Planning& Execution:
Managesand coordinates moderately complex tasks monitoring timelines and deliverablesto ensure timely completion and adherence to requirements for a moderatelysized project or initiative.
Efficientlydelegates monitors and prioritizes work across multiple projects providingtechnical oversight and adjusting plans to address shifts in resources ortimelines.
Collaboration& Partnership:
Collaboratesacross the organization to align on expectations and achieve shared objectives.
Leveragesunderstanding of business leaders stakeholders and/or customers to ensureproposed solutions meet their needs.
Supportsinclusivity by actively seeking and listening to diverse perspectives ensuringothers feel heard and respected.
ProblemSolving:
Identifiesand addresses moderately complex issues by analyzing a wide range of dataand/or information to identify solutions in accordance with standard practices.
Proactivelyescalates unresolved or critical issues with a thorough assessment and suggestspotential solutions.
Reviewscontributes to and documents problem solving strategies.
ContinuousLearning:
Pursueslearning opportunities to expand knowledge and skills and/or tools in new areasand stays abreast of the latest industry trends and best practices.
Proactivelyseeks and leverages ongoing feedback and training to improve skills.
Coachesand mentors junior team members fostering continuous learning and knowledgesharing within and across teams.
ContinuousImprovement:
Developsideas recommends updates and/or collaborates on the implementation of processimprovements to increase the efficiency and effectiveness of processesprotocols and workflows across teams and evaluates the impact on keystakeholders.
Solicitsfeedback from others on ideas for alternative approaches and methods forcontinued improvement.
Performanceand Development:
Contributesto the talent development pipeline by participating in candidate interviewsassessing candidates and providing hiring recommendations.
Qualifications
Disclaimer:
Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements such as immunization/occupational health mandates and/or drug testing requirements.
Range and benefit information provided in this posting are specific to the stated locations only
US: Hiring Range in USD from: $126200 to $264100 per annum. May be eligible for bonus equity and compensation deferral.
Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge skills experience market conditions and locations as well as reflect Oracles differing products industries and lines of business.
Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.
Oracle US offers a comprehensive benefits package which includes the following:
1. Medical dental and vision insurance including expert medical opinion
2. Short term disability and long term disability
3. Life insurance and AD&D
4. Supplemental life insurance (Employee/Spouse/Child)
5. Health care and dependent care Flexible Spending Accounts
6. Pre-tax commuter and parking benefits
7. 401(k) Savings and Investment Plan with company match
8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation.
9. 11 paid holidays
10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.
11. Paid parental leave
12. Adoption assistance
13. Employee Stock Purchase Plan
14. Financial planning and group legal
15. Voluntary benefits including auto homeowner and pet insurance
The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted.
Career Level - IC4
Required Experience:
Staff IC
About Company
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 eve ... View more
