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Machine learning engineer Jobs in Lafayette la
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Machine Learning Engineer
VirtualVocationsLafayette, Louisiana, United States- Promoted
- Promoted
Machine Operator
AT&TLafayette, LouisianaLearning Coach
South Louisiana Community CollegeLafayette, LA- Promoted
Staff Machine Learning Engineer
Home DepotLOUISIANA, US- Promoted
Seasonal Machine Operator
COMPLETEFUL TECHNOLOGIES LLCLafayette, LA, USMachine Repair & Maintenance Technician-Stabil Drill
Superior Energy ServicesLafayette, LA, US- Promoted
Engineer 6 (Regional Engineer Manager)
State of LouisianaLafayette, LA- Promoted
NUCLEAR ENGINEER
NavyBreaux Bridge, LA, United States- Promoted
Project Engineer
Staffing NinjaBroussard, LA, United States- Promoted
Electrical Engineer
Orbital Engineering, Inc.Lafayette, LA, US- Promoted
- Promoted
Electrical Power Engineer
Southern Integrated Solutions & ConsultingBroussard, LA, US- Promoted
Field Engineer
Bluetide CommunicationsBroussard, LA, USMachine Learning Engineer
VirtualVocationsLafayette, Louisiana, United States- Full-time
A company is looking for an Algorithm and Machine Learning Engineer IV / V.Key ResponsibilitiesLead the biosignal-based algorithm development lifecycle for medical devices, including specifications, data curation, development, and maintenanceSelect and implement appropriate methods for problem-solving, balancing deep learning techniques with other methods as neededEnhance internal tools for deep learning and machine learning, ensuring user-friendly and well-documented algorithm implementationsRequired QualificationsMore than 5 years of industry experience in machine learning and deep learning, particularly in health sciences or regulated fieldsExperience with digital signal processing (DSP) and statistics, with a focus on using appropriate tools for various tasksProficiency in PyTorch or other deep learning frameworks for model training and deploymentFamiliarity with recent advances in deep learning, including Transformer / ViT and large-scale modelingExperience with biosignals, medical imaging data, or large time-series datasets is preferred