Regions Bank
Principal Machine Learning Engineer
role at
Regions Bank Thank you for your interest in a career at Regions. We are committed to safeguarding personal information submitted in connection with job opportunities. Information provided will be used to evaluate qualifications and will be stored in accordance with regulatory requirements for a minimum of three years. You may review or update your information in the careers section of the system. Job Description
The Principal Machine Learning Engineer (MLE) supports the Data and Analytics organization by designing, customizing, and implementing data science and analytics platforms for developing and deploying machine learning models. The MLE will use machine learning knowledge and software architecture expertise to design model promotion pipelines, implement dev/ops capabilities for machine learning models, and design processes to ensure provenance across training and inference. The Principal MLE is a forward‑thinking leadership role and will be a key contributor to Regions’ model lifecycle infrastructure strategy. Primary Responsibilities
Designs and implements self-service model deployment strategies Promotes Regions’ cloud strategy and designs cloud-native machine learning workflows Develops tooling to facilitate model development, deployment, and monitoring of data products Develops automated workflows for machine learning pipelines Collaborates with data engineers and data scientists to develop data and model pipelines Creates RESTful APIs for streamlining, monitoring, and reporting on the model lifecycle Designs and implements deployment infrastructure Creates and evangelizes best practices in model operations Fosters a collaborative, open developer environment Leads improvements in methodology or initiatives to address capability gaps or increase efficiency Offers guidance to junior associates for continuous improvement This position is exempt from timekeeping requirements under the Fair Labor Standards Act and is not eligible for overtime pay. This position is incentive eligible. Requirements
Bachelor's degree in Computer Science or a quantitative field Eight (8) years of related experience Preferences
Master's degree Experience with big data and machine learning tools such as Spark, Dask, Kubeflow, Airflow Experience with micro-service architecture and web-services Experience with cloud technologies such as AWS, GCP, Azure, Snowflake, Terraform Working knowledge of machine learning models, common model deployment pitfalls, and inherent complexities Sills and Competencies
A proven track record of working in teams and of leading projects Demonstrated experience with software engineering best practices and implementing software development lifecycles Demonstrated success in one or more of the following programming languages: Python, Golang, Java, JavaScript, Rust and Scala Experience delivering and scaling models in production Experience developing RESTful APIs Experience with Docker/Kubernetes Partnering with Data Scientists, Data Engineers, AI Engineers on delivering production data, machine learning, and AI use cases Building reusable ML and AI deployment pipelines Designing and building architecture and patterns for training, registering, deploying and monitoring models Regions will not sponsor applicants for work visas for this position at this time. Applicants must be authorized to work in the United States on a full-time basis. Other Details
Position Type: Full time Compensation: Pay ranges are job specific and vary by experience, location, and performance. Location: Hoover, Alabama (Riverchase Operations Center) Equal Opportunity Employer/including Disabled/Veterans. Job applications are accepted electronically through Regions’ career site for a minimum of five business days from posting. Referrals increase your chances of interviewing at Regions Bank. Sign in to set job alerts for similar roles.
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role at
Regions Bank Thank you for your interest in a career at Regions. We are committed to safeguarding personal information submitted in connection with job opportunities. Information provided will be used to evaluate qualifications and will be stored in accordance with regulatory requirements for a minimum of three years. You may review or update your information in the careers section of the system. Job Description
The Principal Machine Learning Engineer (MLE) supports the Data and Analytics organization by designing, customizing, and implementing data science and analytics platforms for developing and deploying machine learning models. The MLE will use machine learning knowledge and software architecture expertise to design model promotion pipelines, implement dev/ops capabilities for machine learning models, and design processes to ensure provenance across training and inference. The Principal MLE is a forward‑thinking leadership role and will be a key contributor to Regions’ model lifecycle infrastructure strategy. Primary Responsibilities
Designs and implements self-service model deployment strategies Promotes Regions’ cloud strategy and designs cloud-native machine learning workflows Develops tooling to facilitate model development, deployment, and monitoring of data products Develops automated workflows for machine learning pipelines Collaborates with data engineers and data scientists to develop data and model pipelines Creates RESTful APIs for streamlining, monitoring, and reporting on the model lifecycle Designs and implements deployment infrastructure Creates and evangelizes best practices in model operations Fosters a collaborative, open developer environment Leads improvements in methodology or initiatives to address capability gaps or increase efficiency Offers guidance to junior associates for continuous improvement This position is exempt from timekeeping requirements under the Fair Labor Standards Act and is not eligible for overtime pay. This position is incentive eligible. Requirements
Bachelor's degree in Computer Science or a quantitative field Eight (8) years of related experience Preferences
Master's degree Experience with big data and machine learning tools such as Spark, Dask, Kubeflow, Airflow Experience with micro-service architecture and web-services Experience with cloud technologies such as AWS, GCP, Azure, Snowflake, Terraform Working knowledge of machine learning models, common model deployment pitfalls, and inherent complexities Sills and Competencies
A proven track record of working in teams and of leading projects Demonstrated experience with software engineering best practices and implementing software development lifecycles Demonstrated success in one or more of the following programming languages: Python, Golang, Java, JavaScript, Rust and Scala Experience delivering and scaling models in production Experience developing RESTful APIs Experience with Docker/Kubernetes Partnering with Data Scientists, Data Engineers, AI Engineers on delivering production data, machine learning, and AI use cases Building reusable ML and AI deployment pipelines Designing and building architecture and patterns for training, registering, deploying and monitoring models Regions will not sponsor applicants for work visas for this position at this time. Applicants must be authorized to work in the United States on a full-time basis. Other Details
Position Type: Full time Compensation: Pay ranges are job specific and vary by experience, location, and performance. Location: Hoover, Alabama (Riverchase Operations Center) Equal Opportunity Employer/including Disabled/Veterans. Job applications are accepted electronically through Regions’ career site for a minimum of five business days from posting. Referrals increase your chances of interviewing at Regions Bank. Sign in to set job alerts for similar roles.
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