AI/ML Ops Engineer

Guidehouse•Arlington, VA

28d•Hybrid

About The Position

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.

Requirements

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.

Nice To Haves

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 onâ¯cloud platformsâ¯(e.g., AWS, Azure, GCP) and hybrid cloud deployments, including cloud security (e.g., Managed Identities).
Experience deployingâ¯ML models in production environments with model versioning and rollback strategies.
Understanding ofâ¯data privacy regulationsâ¯(e.g., GDPR, HIPAA) as they relate to ML deployments.
Knowledge ofâ¯network security, including firewalls, VPNs, and secure communication protocols, and experience withâ¯security compliance standardsâ¯(e.g., NIST, ISO 27001, SOC 2).
Exposure toâ¯automated testing frameworksâ¯for infrastructure and security validation.
Experience supportingâ¯DevSecOps and integrating security into CI/CD workflows for AI/ML models.
Experience withâ¯Jenkinsâ¯for building and automating CI/CD pipelines.
Experience utilizing GitHubâ¯for version control, branching strategies, and CI/CD pipeline integration.
Experience withâ¯Dockerâ¯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 inâ¯OpenShiftâ¯for deploying and managing containerized applications in a Kubernetes-based environment.
Knowledge of Infrastructure as Code (IaC) and experience with IaCâ¯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 withâ¯ML model serving frameworksâ¯like MLflow, Seldon, or TensorFlow Serving.
Familiarity withâ¯Linux-based systemsâ¯and shell scripting.
Experience withâ¯monitoring and logging toolsâ¯(e.g., Prometheus, Grafana, ELK stack).

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.

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