AI/ML Engineering Lead

Job Description

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:

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• 16+ years of software or data engineering experience, including 3+ years focused on production ML systems, MLOps, or ML platform engineering.
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• Bachelor's degree in Computer Science, Data Science, Engineering, IT, or a related field; master's degree preferred.
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• Experience building or operating shared enterprise AI/ML platforms supporting multiple teams or agencies.
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• Strong proficiency in Python and experience with PyTorch, TensorFlow, scikit-learn, and Hugging Face.
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• Hands-on experience with MLflow, Kubeflow, Apache Airflow, or equivalent MLOps tools.
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• Experience with AWS SageMaker or equivalent AI/ML services on Azure or GCP.
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• Experience with Docker, Kubernetes, CI/CD pipelines, model registries, experiment tracking, automated testing, deployment, and monitoring.
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• Strong understanding of LLMs, prompt engineering, RAG architecture, model evaluation, and fine-tuning.
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• Experience with data pipelines, feature stores, data quality, data lineage, and governance.
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• Experience with Terraform or Pulumi and GitOps practices.
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• Strong technical leadership, architecture, mentoring, security, and responsible AI experience.
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Preferred Experience:

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• State government, public sector, or highly regulated environments.
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• FedRAMP, NIST AI Risk Management Framework, and applicable cybersecurity and privacy requirements.
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• Responsible AI, model explainability, fairness auditing, bias mitigation, and model risk management.
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• Platform observability, reliability engineering, incident management, disaster recovery, and cloud cost optimization.
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