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. ROBOTIC PROCESS AUTOMATION LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. ROBOTIC PROCESS AUTOMATION LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will ROBOTIC PROCESS AUTOMATION LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract #J-18808-Ljbffr