AWS AI/ML Engineer

Ashburn, VA, US

RavenTek

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Description

Job Title: AWS AI/ML Engineer

Department: Operations – Services 

Reports To: RavenTek Program Manager

Location: Remote 

Schedule: Monday - Friday

Hours: Full-time, 40-hours/week

FLSA Status: Salary, Exempt

Clearance: Public Trust


Position Summary

The AWS AI/ML Engineer is responsible for DHS AI/ML model design and deployment. The AWS AI/ML Engineer will have a deep understanding of AI and the ability to work with stakeholders to implement machine learning. The performance of this position is key to RavenTek's performance on the DCCOCEO contract, and therefore RavenTek's mission to support the customer.


Essential Duties and Responsibilities

  • Install, configure, and maintain Linux servers while ensuring system performance, security, and stability.
  • Develop and deploy Al/ML models using AWS AI/ML services (e.g., SageMaker, Rekognition, Comprehend) and collaborate with data scientists and engineers to implement machine learning solutions.
  • 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.
  • Enter actual time worked, once complete, at the end of the day, or no later than 10:00 a.m. the following workday, and submit timesheets at the end of each pay period.
  • Submit MSRs (weekly, monthly, etc.).
  • Monitor RavenTek email on a regular basis, at least 3 times per week, and respond accordingly.
  • Complete required compliance training as assigned.
  • Other duties as assigned.

Qualifications, Knowledge, and Critical Skills

  • Expertise implementing AWS Al/ML solutions and utilizing containerization platforms such as AWS Cloud Containerization services, Docker, and others.
  • Expertise in AWS Al services and machine learning model deployment.
  • Strong proficiency in containerization technologies, including AWS Cloud Containerization services, and Docker.
  • Solid understanding of networking, security, and system architecture.
  • Knowledge of scripting languages (e.g., Python, Bash).
  • Familiarity with Kubernetes and other container orchestration platforms preferred.

Education & Work Experience

  • Master’s degree in computer science, information technology, or a related field. 
  • Equivalent years of experience may also be substituted for education.
  • Minimum 10+ years of experience directly related to 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.
  • Experience with CI/CD tools and practices.
  • Experience with infrastructure as code tools (e.g., Terraform, CloudFormation).

Certifications, Licenses

  • AWS Certified Solutions Architect or AWS Certified Machine Learning.

Special Requirements

  • Public Trust Clearance 

Work Environment

Employee will be working indoors in an office environment with other people. Potential moderate temperature fluctuations. Typical indoor and computer related noise level, and typical office, paper, and equipment related dust. Exposure to video display terminals occurs on a regular basis.


Physical Demands  

To successfully perform the essential functions of the job, the employee needs to be able to sit at a workstation for extended periods; use hand(s) to handle or feel objects, tools, or controls; reach with hands and arms; talk and hear; see to read printed materials and computer screens; mobility to work in a typical office setting. Ability to work on desktop or laptop computer for extended periods of time reading, reviewing/analyzing information, and may be required to provide recommendations, summaries and/or reports in written format. Must be able to effectively communicate with others verbally and in writing. Employee must be able to lift and/or move moderate amounts of weight, typically up to 20 pounds. Regular and predictable attendance is essential. 


ADA: RavenTek will make reasonable accommodations in compliance with the Americans with Disabilities Act of 1990.


EEO/AA: RavenTek does not discriminate based on race, color, national origin, sex, religion, age, disability, sexual orientation, gender identity, veteran status, height, weight, or marital status in employment or the provision of services and is an equal access/equal opportunity/affirmative action employer.


This job description is not intended to be an all-inclusive list of duties and standards of the position and will be reviewed periodically as duties and responsibilities change with business necessity. Essential job functions are subject to modification. Incumbents will follow any other instructions, and perform any other related duties, as assigned by their supervisor.

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Tags: Architecture AWS CI/CD CloudFormation Computer Science Docker ECS Kubernetes Linux Machine Learning ML models Model deployment Model design Pipelines Python SageMaker Security Terraform

Perks/benefits: Gear

Region: North America
Country: United States

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