Sr. Cloud Support Engineer (Remote)
Sierra7 requires a Senior Cloud Support Engineer to add to their Service Design team.
The resource will focus on supporting Artificial Intelligence and Machine Learning technologies in the AWS environment specific to Amazon SageMaker services.
They will work in partnership with the AI-ML Service Manager.
The AI-ML Service Manager will drive overall strategic planning for that technology for CHS, as well as perform initial evaluation of use cases and formulate recommended approaches to customer investigations utilizing AI and ML (or even if those techniques are inappropriate for the customer's goals.
) The AI-ML support engineer will as needed do follow-on engagements with customers to help them use SageMaker and other AI services in the AWS environment.
This could include introducing the customer to using the environment, performing coding required to help them prepare data, ensuring they use SageMaker properly in line with the strategies laid out by the AI-ML Service Manager, etc.
Additionally, the Support Engineer should work with customers as appropriate to help show or teach them how the AI/ML tools are used with the goal that in future they may be positioned to no need similar support in part or at all in future ML/AI endeavors.
Essential Engineering
Qualifications:
Proven ability to work with AWS SageMaker to advance machine learning investigations.
Manage version control system with strong understanding of git branching and merging strategies Understanding of building, training, and deploying AIML models in an AWS environment Deliver all solutions as code which is well-documented and includes plan for full-service lifecycle management In-depth knowledge of Python scripting for purpose of model development Understanding of Jupyter Notebooks and integration with Amazon SageMaker Notebooks Experience with docker solutions to include AWS ECS/Batch or AWS EKSBasic
Qualifications:
US Citizen Ability to pass a federal government background investigation Minimum Years of
Experience:
Must have minimum of 3 years of experience in Cloud / AWS Engineering/Development with 3
years in overall AIML development Minimum Education:
BS Degree in related discipline or equivalent, additional experience Must have at least 2 Associate-Level AWS Certificationso Solutions Architecto Developer/SysOps Capable of multi-tasking balancing multiple projects and timelines simultaneously In-depth understanding of CloudFormation and CloudFormation StackSets Extensive experience with git version control and CICD practices Advanced level proficiency in one scripting language (Python, PowerShell) Proficiency with Gitlab CI and configuration of GitLab Runner Experience with Docker and Serverless environments (Lambda)Preferred
Qualifications:
Master's degree or higher in engineering or information systems study AWS Professional-Level Certification (Solutions Architect or DevOps) In-depth knowledge and experience with learning frameworks to include TensorFlow, PyTorch, Apache MXNet, Chainer, Keras, Gluon, Horovod, Scikit-learn, and Deep Graph LibraryACTIVE SECURITY CLEARANCE, CLEARANCE WITHIN DOI PREFERREDDisclaimerThe above statements are intended to describe the general nature and level of work being performed by people assigned to this classification.
They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified.
Equal Opportunity Employer Veterans DisabledIndeedSierra7Sierra7 requires a Senior Cloud Support Engineer to add to their Service Design team.
The resource will focus on supporting Artificial Intelligence and Machine Learning technologies in the AWS environment specific to Amazon SageMaker services.
They will work in partnership with the AI-ML Service Manager.
The AI-ML Service Manager will drive overall strategic planning for that technology , as well as perform initial evaluation of use cases and formulate recommended approaches to customer investigations utilizing AI and ML (or even if those techniques are inappropriate for the customer's goals.
) The AI-ML support engineer will as needed do follow-on engagements with customers to help them use SageMaker and other AI services in the AWS environment.
This could include introducing the customer to using the CHS environment, performing coding required to help them prepare data, ensuring they use SageMaker properly in line with the strategies laid out by the AI-ML Service Manager, etc.
Additionally, the Support Engineer should work with customers as appropriate to help show or teach them how the AI/ML tools are used with the goal that in future they may be positioned to no need similar support in part or at all in future ML/AI endeavors.
Essential Engineering
Qualifications:
Proven ability to work with AWS SageMaker to advance machine learning investigations.
Manage version control system with strong understanding of git branching and merging strategies Understanding of building, training, and deploying AIML models in an AWS environment Deliver all solutions as code which is well-documented and includes plan for full-service lifecycle management In-depth knowledge of Python scripting for purpose of model development Understanding of Jupyter Notebooks and integration with Amazon SageMaker Notebooks Experience with docker solutions to include AWS ECS/Batch or AWS EKSBasic
Qualifications:
US Citizen Ability to pass a federal government background investigation Minimum Years of
Experience:
Must have minimum of 3 years of experience in Cloud / AWS Engineering/Development with 3
years in overall AIML development Minimum Education:
BS Degree in related discipline or equivalent, additional experience Must have at least 2 Associate-Level AWS Certificationso Solutions Architecto Developer/SysOps Capable of multi-tasking balancing multiple projects and timelines simultaneously In-depth understanding of CloudFormation and CloudFormation StackSets Extensive experience with git version control and CICD practices Advanced level proficiency in one scripting language (Python, PowerShell) Proficiency with Gitlab CI and configuration of GitLab Runner Experience with Docker and Serverless environments (Lambda)Preferred
Qualifications:
Master's degree or higher in engineering or information systems study AWS Professional-Level Certification (Solutions Architect or DevOps) In-depth knowledge and experience with learning frameworks to include TensorFlow, PyTorch, Apache MXNet, Chainer, Keras, Gluon, Horovod, Scikit-learn, and Deep Graph LibraryInitial Deliverables One month after implementation, become orientated regarding the CHS technical architecture they will be working within.
Engage with the CHS AI-ML Service Manager and CHS Director to confirm respective roles and strategies for engagement with customers.
Two months after implementation, engage with one or more customers to help them advance their ML/AI initiatives.
DisclaimerThe above statements are intended to describe the general nature and level of work being performed by people assigned to this classification.
They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified.
Equal Opportunity Employer Veterans Disabled.
Estimated Salary: $20 to $28 per hour based on qualifications.
The resource will focus on supporting Artificial Intelligence and Machine Learning technologies in the AWS environment specific to Amazon SageMaker services.
They will work in partnership with the AI-ML Service Manager.
The AI-ML Service Manager will drive overall strategic planning for that technology for CHS, as well as perform initial evaluation of use cases and formulate recommended approaches to customer investigations utilizing AI and ML (or even if those techniques are inappropriate for the customer's goals.
) The AI-ML support engineer will as needed do follow-on engagements with customers to help them use SageMaker and other AI services in the AWS environment.
This could include introducing the customer to using the environment, performing coding required to help them prepare data, ensuring they use SageMaker properly in line with the strategies laid out by the AI-ML Service Manager, etc.
Additionally, the Support Engineer should work with customers as appropriate to help show or teach them how the AI/ML tools are used with the goal that in future they may be positioned to no need similar support in part or at all in future ML/AI endeavors.
Essential Engineering
Qualifications:
Proven ability to work with AWS SageMaker to advance machine learning investigations.
Manage version control system with strong understanding of git branching and merging strategies Understanding of building, training, and deploying AIML models in an AWS environment Deliver all solutions as code which is well-documented and includes plan for full-service lifecycle management In-depth knowledge of Python scripting for purpose of model development Understanding of Jupyter Notebooks and integration with Amazon SageMaker Notebooks Experience with docker solutions to include AWS ECS/Batch or AWS EKSBasic
Qualifications:
US Citizen Ability to pass a federal government background investigation Minimum Years of
Experience:
Must have minimum of 3 years of experience in Cloud / AWS Engineering/Development with 3
years in overall AIML development Minimum Education:
BS Degree in related discipline or equivalent, additional experience Must have at least 2 Associate-Level AWS Certificationso Solutions Architecto Developer/SysOps Capable of multi-tasking balancing multiple projects and timelines simultaneously In-depth understanding of CloudFormation and CloudFormation StackSets Extensive experience with git version control and CICD practices Advanced level proficiency in one scripting language (Python, PowerShell) Proficiency with Gitlab CI and configuration of GitLab Runner Experience with Docker and Serverless environments (Lambda)Preferred
Qualifications:
Master's degree or higher in engineering or information systems study AWS Professional-Level Certification (Solutions Architect or DevOps) In-depth knowledge and experience with learning frameworks to include TensorFlow, PyTorch, Apache MXNet, Chainer, Keras, Gluon, Horovod, Scikit-learn, and Deep Graph LibraryACTIVE SECURITY CLEARANCE, CLEARANCE WITHIN DOI PREFERREDDisclaimerThe above statements are intended to describe the general nature and level of work being performed by people assigned to this classification.
They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified.
Equal Opportunity Employer Veterans DisabledIndeedSierra7Sierra7 requires a Senior Cloud Support Engineer to add to their Service Design team.
The resource will focus on supporting Artificial Intelligence and Machine Learning technologies in the AWS environment specific to Amazon SageMaker services.
They will work in partnership with the AI-ML Service Manager.
The AI-ML Service Manager will drive overall strategic planning for that technology , as well as perform initial evaluation of use cases and formulate recommended approaches to customer investigations utilizing AI and ML (or even if those techniques are inappropriate for the customer's goals.
) The AI-ML support engineer will as needed do follow-on engagements with customers to help them use SageMaker and other AI services in the AWS environment.
This could include introducing the customer to using the CHS environment, performing coding required to help them prepare data, ensuring they use SageMaker properly in line with the strategies laid out by the AI-ML Service Manager, etc.
Additionally, the Support Engineer should work with customers as appropriate to help show or teach them how the AI/ML tools are used with the goal that in future they may be positioned to no need similar support in part or at all in future ML/AI endeavors.
Essential Engineering
Qualifications:
Proven ability to work with AWS SageMaker to advance machine learning investigations.
Manage version control system with strong understanding of git branching and merging strategies Understanding of building, training, and deploying AIML models in an AWS environment Deliver all solutions as code which is well-documented and includes plan for full-service lifecycle management In-depth knowledge of Python scripting for purpose of model development Understanding of Jupyter Notebooks and integration with Amazon SageMaker Notebooks Experience with docker solutions to include AWS ECS/Batch or AWS EKSBasic
Qualifications:
US Citizen Ability to pass a federal government background investigation Minimum Years of
Experience:
Must have minimum of 3 years of experience in Cloud / AWS Engineering/Development with 3
years in overall AIML development Minimum Education:
BS Degree in related discipline or equivalent, additional experience Must have at least 2 Associate-Level AWS Certificationso Solutions Architecto Developer/SysOps Capable of multi-tasking balancing multiple projects and timelines simultaneously In-depth understanding of CloudFormation and CloudFormation StackSets Extensive experience with git version control and CICD practices Advanced level proficiency in one scripting language (Python, PowerShell) Proficiency with Gitlab CI and configuration of GitLab Runner Experience with Docker and Serverless environments (Lambda)Preferred
Qualifications:
Master's degree or higher in engineering or information systems study AWS Professional-Level Certification (Solutions Architect or DevOps) In-depth knowledge and experience with learning frameworks to include TensorFlow, PyTorch, Apache MXNet, Chainer, Keras, Gluon, Horovod, Scikit-learn, and Deep Graph LibraryInitial Deliverables One month after implementation, become orientated regarding the CHS technical architecture they will be working within.
Engage with the CHS AI-ML Service Manager and CHS Director to confirm respective roles and strategies for engagement with customers.
Two months after implementation, engage with one or more customers to help them advance their ML/AI initiatives.
DisclaimerThe above statements are intended to describe the general nature and level of work being performed by people assigned to this classification.
They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified.
Equal Opportunity Employer Veterans Disabled.
Estimated Salary: $20 to $28 per hour based on qualifications.
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