Xprotege Institute of Technology and Management
AI/ML Engineering Lead
Linthicum Heights, District of Columbia, US
Role snapshot
Xprotege Institute of Technology and Management is hiring a AI/ML Engineering Lead on a full-time basis. This is an on-site role based in Linthicum Heights, District of Columbia, US.
- Company
- Xprotege Institute of Technology and Management
- Location
- Linthicum Heights, District of Columbia, US
- Work mode
- On-site
- Job type
- Full-time
- Experience
- 16+ years
- Posted
- Nov 1, 2026
Who this role suits
Experienced professionals who can lead projects, set direction and be accountable for outcomes, not just tasks.
How to prepare your application
- Prepare examples of decisions you drove, how you measured the result, and how you worked with other teams.
- Be ready to discuss trade-offs and scope, not only the tools you have used.
- Read what Xprotege Institute of Technology and Management publishes about its product or team, so you can say clearly why this role and this company.
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About the role
Position: AI/ML Engineering Lead
Location: Linthicum Heights, MD
Work Arrangement: Onsite
Looking for Local Candidates Only
Position Overview:
The AI/ML Engineering Lead will lead the architecture, development, implementation, and governance of a shared enterprise AI/ML platform supporting multiple state agencies. This role focuses on ML engineering, MLOps, cloud infrastructure, data engineering, and Generative AI to deliver secure, scalable, reliable, and responsible AI/ML solutions.
Key Requirements:
- 16+ years of software or data engineering experience, including 3+ years focused on production ML systems, MLOps, or ML platform engineering.
- Bachelor's degree in Computer Science, Data Science, Engineering, IT, or a related field; master's degree preferred.
- Experience building or operating shared enterprise AI/ML platforms supporting multiple teams or agencies.
- Strong proficiency in Python and experience with PyTorch, TensorFlow, scikit-learn, and Hugging Face.
- Hands-on experience with MLflow, Kubeflow, Apache Airflow, or equivalent MLOps tools.
- Experience with AWS SageMaker or equivalent AI/ML services on Azure or GCP.
- Experience with Docker, Kubernetes, CI/CD pipelines, model registries, experiment tracking, automated testing, deployment, and monitoring.
- Strong understanding of LLMs, prompt engineering, RAG architecture, model evaluation, and fine-tuning.
- Experience with data pipelines, feature stores, data quality, data lineage, and governance.
- Experience with Terraform or Pulumi and GitOps practices.
- Strong technical leadership, architecture, mentoring, security, and responsible AI experience.
Preferred Experience:
- State government, public sector, or highly regulated environments.
- FedRAMP, NIST AI Risk Management Framework, and applicable cybersecurity and privacy requirements.
- Responsible AI, model explainability, fairness auditing, bias mitigation, and model risk management.
- Platform observability, reliability engineering, incident management, disaster recovery, and cloud cost optimization.