AI​/ML Ops Engineer

Job Family
:

Data Science & Analysis

Travel Required
:

None

Clearance Required
:

Active Secret

• 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 Dev Sec Ops  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.

• 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/Power Shell.
• 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.

• 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 oncloud 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 Dev Sec Ops  and integrating security into CI/CD workflows for AI/ML models.
• Experience with Jenkins for building and automating CI/CD pipelines.
• Experience utilizing Git Hub for version control, branching strategies, and CI/CD pipeline integration.
• Experience with Docker for containerizing ML models and managing container life cycles, including building Docker images.
• Experience working with YAML files.
• Knowledge Power Shell and command-line scripting.
• Experience managing cloud resources by maintaining and optimizing cloud environments for reliability, scalability, and cost.
• Experience in Open Shift 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 Tensor Flow Serving.
• Familiarity with Linux-based systems and shell scripting.
• Experience with monitoring and logging tools(e.g., Prometheus, Grafana, ELK stack).

Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.

Benefits include:

• Medical, Rx, Dental & Vision Insurance
• Personal and Family Sick Time & Company Paid Holidays
• Parental Leave
• 401(k) Retirement Plan
• Group Term Life and Travel…