Guidehouse · 2 months ago
AI/ML Ops Engineer
US - VA, Arlington
Full-time
Onsite
Mid Level
3+ years expGuidehouse is a leading consulting firm, and they are seeking an AI/ML Ops Engineer. The role involves building and maintaining CI/CD pipelines for AI and ML applications, operationalizing ML models, and collaborating with data scientists to deliver tailored solutions.
AdviceConsultingManagement Consulting
No H1B
Security Clearance RequiredU.S. Citizen Only
Responsibilities
Build, automate, and maintain CI/CD pipelines for artificial intelligence (AI) and machine learning (ML) and software applications
Containerize applications/models and deploy them to cloud environments (e.g., Azure, AWS, etc.)
Operationalize ML models: packaging, versioning, testing, deployment, and monitoring
Support data scientists and developers in taking developed code to staging to production
Ensure security integration between DevSecOps pipelines and cloud services and configure monitoring and alerting for applications, pipelines and ML models in production
Design and document technical process flows and diagrams, present them to clients, and answer questions about them
Ensure AI/ML deployments adhere to commercial and public sector guidelines, security practices, policies and standards, delivering responsible use of AI
Collaborate with data scientists and other adjacent roles
Provide technical guidance and mentorship to team members
Develop trusted relationships with clients by understanding their mission, challenges, and goals, and delivering tailored solutions that drive innovation in AI/ML and data science
Support business development efforts (e.g., responding to RFPs/RFIs, developing white papers, creating pitch decks and capability briefings, etc.)
Support internal firm initiatives
Continue to develop professionally in technical skills, consulting skills, and client domain knowledge
Qualification
Required
An ACTIVE and MAINTAINED 'SECRET' Federal or DoD security clearance
Bachelor's degree is required
THREE (3) years of relevant professional experience
Proficiency in Git and modern branching/versioning workflows
Experience with CI/CD tools (Azure preferred)
Experience with ML model containerization and the ability to build and deploy Docker containers and understand container networking and storage
Experience in Azure (or AWS) cloud environment, optimizing compute, networking, and storage
Proficiency in programming in Python, with experience scripting in Bash/PowerShell
Understanding of Agile principles and methodology
Ability to understand client mission and business processes and adapt solutions and approaches accordingly to be successful
Ability to operate independently and collaboratively in small teams
Strong communication and presentation skills for both technical and non-technical audiences
Ability to think strategically and drive innovation
Ability to operate successfully on remote, hybrid, or on-site projects in the DC metro area
Preferred
Master's degree
SIX (6) years of relevant professional experience
Relevant experience supporting Department of State or other Federal Government organizations
Experience with deploying AI/ML models on cloud platforms (e.g., AWS, Azure, GCP) and hybrid cloud deployments, including cloud security (e.g., Managed Identities)
Experience deploying ML models in production environments with model versioning and rollback strategies
Understanding of data privacy regulations (e.g., GDPR, HIPAA) as they relate to ML deployments
Knowledge of network security, including firewalls, VPNs, and secure communication protocols, and experience with security compliance standards (e.g., NIST, ISO 27001, SOC 2)
Exposure to automated testing frameworks for infrastructure and security validation
Experience supporting DevSecOps and integrating security into CI/CD workflows for AI/ML models
Experience with Jenkins for building and automating CI/CD pipelines
Experience utilizing GitHub for version control, branching strategies, and CI/CD pipeline integration
Experience with Docker for containerizing ML models and managing container lifecycles, including building Docker images
Experience working with YAML files
Knowledge PowerShell and command-line scripting
Experience managing cloud resources by maintaining and optimizing could environments for reliability, scalability, and cost
Experience in OpenShift for deploying and managing containerized applications in a Kubernetes-based environment
Knowledge of Infrastructure as Code (IaC) and experience with IaC tools such as Terraform and Ansible
Knowledge of Function Apps
Experience working with Virtual Machines and configuring them to be scalable, Azure Blob Storage, working with Desired State Configurations
Familiarity with ML model serving frameworks like MLflow, Seldon, or TensorFlow Serving
Familiarity with Linux-based systems and shell scripting
Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack)
Benefits
Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Parental Leave
401(k) Retirement Plan
Group Term Life and Travel Assistance
Voluntary Life and AD&D Insurance
Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts
Transit and Parking Commuter Benefits
Short-Term & Long-Term Disability
Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Care.com annual membership
Employee Assistance Program
Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.)
Position may be eligible for a discretionary variable incentive bonus
Company
Guidehouse
Guidehouse offers consulting services for public and commercial markets with expertise in management, technology, and risk consulting.
10001+ employees
Funding
Current Stage
Late StageTotal Funding
$0.75MKey Investors
Mission Daybreak
2023-11-06Acquired
2023-02-16Grant· $0.75M
Leadership Team
Scott McIntyre
Chairman and CEO
Alicia Harkness
Partner
Recent News
Washington Technology
2026-01-16
Washington Technology
2026-01-09
Company data provided by crunchbase