Sourcefly
AWS AI/ML Engineer
Sourcefly, Virginia, Minnesota, United States, 55792
We are seeking an
AWS AI/ML Engineer
with a strong focus on AWS AI/ML and containerization technologies for development, modernization, and migration in support of a government multi-cloud environment with 30+ customer tenants and growing. Aside from technical qualifications, application should have effective communication skills, both written and verbal.
The applicant must have extensive cloud knowledge and experience with integration, system analysis or programming experience, including developing cloud systems requirements and design specification. A passion for performance, strong desire for quality conformance, excellent problem-solving skills and attention to detail are prerequisites for this position.
LOCATION: Remote (but must reside and perform all work within the United States)
WORK HOURS: This position requires working online from 8:00 AM Eastern to 5:00 PM Eastern
Key Responsibilities:
Develop and deploy AI/ML models using AWS AI/ML services (e.g., SageMaker, Rekognition, Comprehend) and collaborate with data scientists and engineers to implement machine learning solutions.
Install, configure, and maintain Linux servers while ensuring system performance, security, and stability.
Design, implement, and manage containerized applications using AWS Cloud Containerization services (e.g., ECS, EKS) and Docker, developing CI/CD pipelines for automated deployment and scaling.
Work closely with cross-functional teams to understand project requirements and deliver robust solutions, documenting system configurations, procedures, and best practices.
Provide technical guidance and mentorship to junior team members.
Requirements:
Minimum 10+ years of experience directly related work in area of expertise
5+ years of experience as an AWS Engineer operating within a Linux environment managing and optimizing Linux systems for AWS
Expertise implementing AWS AI/ML solutions and utilizing containerization platforms such as AWS Cloud Containerization services, Docker, and others.
Master's degree in Computer Science, Information Technology, or a related field. (Equivalent years of experience may also be substituted for education)
Expertise in AWS AI services and machine learning model deployment.
Strong proficiency in containerization technologies, including AWS Cloud Containerization services and Docker.
Experience with CI/CD tools and practices.
Solid understanding of networking, security, and system architecture.
Preferred Skills:
AWS Certified Solutions Architect or AWS Certified Machine Learning.
Familiarity with Kubernetes and other container orchestration platforms.
Experience with infrastructure as code tools (e.g., Terraform, CloudFormation).
Knowledge of scripting languages (e.g., Python, Bash).
Security Clearance Requirements:
Public Trust- Ability to obtain a DHS Public Trust Security Clearance (called “Entry on Duty”)
US Citizenship
required
– personnel with Permanent Resident (Green Cards) or Work Visas are not eligible for this position
#J-18808-Ljbffr
AWS AI/ML Engineer
with a strong focus on AWS AI/ML and containerization technologies for development, modernization, and migration in support of a government multi-cloud environment with 30+ customer tenants and growing. Aside from technical qualifications, application should have effective communication skills, both written and verbal.
The applicant must have extensive cloud knowledge and experience with integration, system analysis or programming experience, including developing cloud systems requirements and design specification. A passion for performance, strong desire for quality conformance, excellent problem-solving skills and attention to detail are prerequisites for this position.
LOCATION: Remote (but must reside and perform all work within the United States)
WORK HOURS: This position requires working online from 8:00 AM Eastern to 5:00 PM Eastern
Key Responsibilities:
Develop and deploy AI/ML models using AWS AI/ML services (e.g., SageMaker, Rekognition, Comprehend) and collaborate with data scientists and engineers to implement machine learning solutions.
Install, configure, and maintain Linux servers while ensuring system performance, security, and stability.
Design, implement, and manage containerized applications using AWS Cloud Containerization services (e.g., ECS, EKS) and Docker, developing CI/CD pipelines for automated deployment and scaling.
Work closely with cross-functional teams to understand project requirements and deliver robust solutions, documenting system configurations, procedures, and best practices.
Provide technical guidance and mentorship to junior team members.
Requirements:
Minimum 10+ years of experience directly related work in area of expertise
5+ years of experience as an AWS Engineer operating within a Linux environment managing and optimizing Linux systems for AWS
Expertise implementing AWS AI/ML solutions and utilizing containerization platforms such as AWS Cloud Containerization services, Docker, and others.
Master's degree in Computer Science, Information Technology, or a related field. (Equivalent years of experience may also be substituted for education)
Expertise in AWS AI services and machine learning model deployment.
Strong proficiency in containerization technologies, including AWS Cloud Containerization services and Docker.
Experience with CI/CD tools and practices.
Solid understanding of networking, security, and system architecture.
Preferred Skills:
AWS Certified Solutions Architect or AWS Certified Machine Learning.
Familiarity with Kubernetes and other container orchestration platforms.
Experience with infrastructure as code tools (e.g., Terraform, CloudFormation).
Knowledge of scripting languages (e.g., Python, Bash).
Security Clearance Requirements:
Public Trust- Ability to obtain a DHS Public Trust Security Clearance (called “Entry on Duty”)
US Citizenship
required
– personnel with Permanent Resident (Green Cards) or Work Visas are not eligible for this position
#J-18808-Ljbffr