TBK Bank, SSB
Machine Learning Engineer (MLE) - Open to Remote
TBK Bank, SSB, Dallas, Texas, United States, 75215
We’reAs an ML Engineer, you will play a crucial role in advancing logistics technology by developing and optimizing ML models that address new business challenges in freight. You will be responsible for ensuring the efficiency and accuracy of our deployed models, scaling their performance, and automating ML pipelines.
hiring experienced Machine Learning Engineer to join our growing team at Triumph Intelligence. Scale and optimize the performance of existing models (RPS, memory consumption) for strict latency requirements and high precision.Strong communication skills with the ability to explain the "why" behind technical decisions to diverse audiences.4+ years of software engineering experience. Deep knowledge of core tools including Python, SQL, Strong visualization and storytelling skills such as Matplotlib and SeabornEnd-to-end ML development and deployment experience. Familiarity with ML algorithms and methodologies such as neural networks, time series, gradient boosting, and random forest. Experience developing and deploying production-grade ML solutions using Docker, Kubernetes, AWS S3, and thorough unit testing. Ability to work core hours on Eastern Standard Time (EST) to facilitate a 3–4 hour daily overlap with our EU-based engineering team.Experience leading an engineering team or running consulting practice.Experience optimizing and monitoring model behavior using sophisticated. hyperparameter tuning methods and specialized anomaly detection techniques.Familiarity with AWS as a primary cloud platform for deploying and scaling ML workloads. #J-18808-Ljbffr
hiring experienced Machine Learning Engineer to join our growing team at Triumph Intelligence. Scale and optimize the performance of existing models (RPS, memory consumption) for strict latency requirements and high precision.Strong communication skills with the ability to explain the "why" behind technical decisions to diverse audiences.4+ years of software engineering experience. Deep knowledge of core tools including Python, SQL, Strong visualization and storytelling skills such as Matplotlib and SeabornEnd-to-end ML development and deployment experience. Familiarity with ML algorithms and methodologies such as neural networks, time series, gradient boosting, and random forest. Experience developing and deploying production-grade ML solutions using Docker, Kubernetes, AWS S3, and thorough unit testing. Ability to work core hours on Eastern Standard Time (EST) to facilitate a 3–4 hour daily overlap with our EU-based engineering team.Experience leading an engineering team or running consulting practice.Experience optimizing and monitoring model behavior using sophisticated. hyperparameter tuning methods and specialized anomaly detection techniques.Familiarity with AWS as a primary cloud platform for deploying and scaling ML workloads. #J-18808-Ljbffr