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Mid-Level AI Engineer — Remote Cloud-Native ML Federal

Remote / Online - Candidates ideally in
McLean, Fairfax County, Virginia, USA
Listing for: Credence
Remote/Work from Home position
Listed on 2026-06-04
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Position: Mid-Level AI Engineer — Remote Cloud-Native ML for Federal

Overview

Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose.

We’ve been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges.

Position

Summary

Credence has an immediate need for a Mid-Level AI Engineer to join our growing AI and Automation practice. You will be a technical anchor in our AI and Automation practice. You’ll apply foundational AI/ML skills to build and deploy data-driven solutions. Under mentorship from senior AI leaders, you’ll drive model development life cycles and collaborate across engineering, data, and stakeholder teams to deliver high-impact, cloud-native AI capabilities that advance federal missions.

Responsibilities

include, but are not limited to the duties listed below
  • AI Model Development & Integration
    Support end-to-end AI development: data prep, feature engineering, model training, evaluation, and integration into production pipelines.
  • Collaborative Engineering
    Work alongside data engineers, software engineers, and data scientists to embed AI into scalable systems and applications.
  • Cloud & MLOps Enablement
    Help automate model deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, and container orchestration tools.
  • Generative AI & LLM Usage
    Contribute to projects using generative AI and LLMs, helping to prototype, customize, and refine models.
  • Production Monitoring & Optimization
    Monitor AI systems post-deployment, perform performance tuning, and apply best practices for reliability and scalability.
  • Technical Rigor & Documentation
    Write clean, well-documented code following industry and federal guidelines; support reproducible development.
  • Professional Growth
    Stay current on AI/ML trends and tools, and actively learn from senior team members through mentorship and technical design reviews.
Qualifications
  • U.S. citizenship with the ability to obtain a public trust.
  • Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or a related field.
  • 3–5 years of hands‑on experience delivering AI/ML solutions.
  • Familiarity with OpenAI, Claude Sonnet, Claude Opus, and other AI engines.
  • Strong Python proficiency and familiarity with AI/ML libraries (e.g., Tensor Flow, PyTorch, scikit‑learn).
  • Understanding of supervised and unsupervised learning techniques.
  • Experience working with cloud platforms (AWS, Azure, or GCP) and container tools (Docker, Kubernetes).
  • Familiarity with CI/CD pipelines and basic MLOps workflows.
  • Experience or interest in generative AI and working with LLMs.
  • Experience with VS Code and AI extensions like Cline and Claude Code, in addition to QDeveloper.
  • Strong communication skills and client‑oriented mindset.
Preferred
  • Experience with Bedrock, Strands, Q Developer, Kiro, Agent Core Gateway.
  • Exposure to AWS Serverless technologies including ones that enable Event based architecture (important for Agentic AI systems).
  • Experience with IaC tools (AWS CDK, Terraform, Cloud Formation) or model monitoring tools.
  • Exposure to data engineering concepts or data pipeline optimization.
  • Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks.
  • Knowledge of MCP servers and how they can be used for reusable archetypes between teams.
Why This Role Matters
  • Real-World Impact — Your work will support defense and health agencies where AI solutions directly contribute to national security and public well‑being.
  • Growth‑Oriented Environment — Learn from technical leaders, expand into LLM and generative AI, and build expertise in cloud‑first MLOps.
  • Culture of Empowerment — You’ll be part of a team that values innovation, trust, collaboration, and mission success.
Benefits
  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • Family Leave (Maternity, Paternity)
  • Short Term & Long Term Disability
  • Training & Development
  • Work From Home
  • Wellness Resources
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