Mid AI/ML Engineer

The candidate must hold and provide verifiable evidence of at least one relevant AI/ML credential, such as an Azure AI/Generative AI certification, AWS Generative AI or ML certification, Google Cloud Generative AI/ML credential, Databricks Generative AI Engineer credential, Snowflake data credential, NVIDIA generative AI credential, CAIP, or equivalent.

• 3+ years relevant experience, including 2+ years AI/ML implementation.
• Hands-on Python, APIs, data pipelines, Git, testing and cloud delivery.
• Experience with LLM, RAG, NLP, document intelligence or predictive ML.
• Build AI applications, automation, integrations and production solutions.
• Experience with MLOps/DevSecOps, CI/CD, monitoring and evaluation.
• Knowledge of security, PII, accessibility and regulated environments.

Preferred qualifications

• Experience with AWS, Azure, Google Cloud, or FedRAMP-authorized AI services.
• Experience with vector databases, embedding pipelines, reranking, evaluation tooling, and LLM observability.
• Experience supporting Federal ATO/RMF, SBOM creation, vulnerability scanning, and Section 508 remediation.
• Experience in OSHA, grants oversight, workforce programs, compensation claims, fraud detection, document processing, or public-facing information systems.

Required certification evidence

The candidate must hold and provide verifiable evidence of at least one relevant AI/ML credential, such as an Azure AI/Generative AI certification, AWS Generative AI or ML certification, Google Cloud Generative AI/ML credential, Databricks Generative AI Engineer credential, Snowflake data credential, NVIDIA generative AI credential, CAIP, or equivalent. Evidence must be supplied at onboarding and annually thereafter; self-attestation is not sufficient.