ML Engineer
- Ensure that ML models can be effectively developed, deployed, managed, and monitored in Production environments.
- Productionize ML models – integrate trained ML models with Production systems
- Build and manage ML pipelines – design, build, and maintain automated pipelines including data ingestion, data preprocessing, model training, validation, and deployment utilizing CI/CD practices.
- Infrastructure management – set up and manage infrastructure for ML workloads utilizing cloud platforms and containerization technologies.
- Monitoring and alerting – implement monitoring systems to track performance of ML models in Production
- Automation – automate various tasks within the ML workflow to improve efficiency and reproducibility
- Performance optimization – identify ways to optimize the performance, efficiency, and scalability of ML models and their supporting infrastructure
- All other duties as assigned or directed.
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
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