Senior AI/ML Operations Specialist

Title: AI/ML Operations Specialist Roles And Responsibilities • Lead 12+ monthly training sessions (live demos, Q&A) with H2O low-code tools, achieving >95% participant satisfaction. • Create the Knowledge Transfer Plan (90 days) and 100+ pages of documentation (e.g., AI Ops Manual) on SharePoint, updating annually with H2O TrendSync (92% accuracy). • Engineer 500+ prompts with Reinforcement Learning from Human Feedback (RLHF) via Azure ML, targeting >80% response relevancy. • Tune multi-modal AI (Text-to-Text, Image-to-Text) with H2O Document AI (OCR/NLP) and TensorFlow CNNs for 5,000+ regulatory documents. Produce monthly AI Pre-Generative Training Results reports (Power BI) and develop user education content (guides, webinars) for 500+ user Design and deploy LLMs (e.g., GPT-4o, LLaMA) with H2O AI Cloud (Kubernetes-based MLOps) and RESTful APIs, integrating with legacy Java/.NET systems. Optimize for <500ms latency and 99.95% uptime using Dynatrace/AppDynamics, managing updates with Azure DevOps rollbacks. Author the Operation & Maintenance (O&M) Handbook (120 days), detailing 50+ API specs and 20+ dashboards Craft AI/ML policies using H2O Driverless AI (AutoML) to generate 1,200+ compliance features across 135+ applications in a hybrid cloud. Mitigate risks like regulatory non-compliance and model drift with SHAP/LIME (bias detection) and Azure Purview (FISMA-compliant data lineage). Deliver the Continuous Improvement Program Plan (CIPP) in 120 days and drive annual updates via Agile sprints and Dynatrace monitoring Secret Clearance Required: TBD Familiarity With Tools • Dynatrace • AppDynamics • Azure Monitor • Azure OpenAI • Microsoft ML Studio • Kubernetes • Databricks • CI/CD pipelines • Git • AI governance tools • IT security protocols Required Skills/ Experience • 7+ years in AI/ML development, deployment, and tuning (e.g., LLMs like GPT-4, LLaMA). • Hands-on success in federal projects with Azure/AWS, hybrid clouds, and compliance (e.g., FISMA, NIST 800-53). • Proven ability to integrate AI with legacy systems (Java/.NET) and manage multi-modal workflows • Mastery of Python, TensorFlow, PyTorch, and H2O.ai tools (Driverless AI, Document AI, AI Cloud). • Proficiency in Kubernetes, RESTful APIs, Azure OpenAI, AWS SageMaker, and monitoring tools (Dynatrace, AppDynamics). • Experience with data pipelines (Azure Data Factory, AWS Glue) and prompt engineering/RLHF. • TensorFlow Developer Certificate, AWS Certified Machine Learning - Specialty, Microsoft Certified: Azure AI Engineer Associate, or AWS Certified Solutions Architect - Professional. Nice-to-Haves • 10+ years in AI architecture or federal financial regulation projects (e.g., OCC, Treasury). • Certifications: PMP, ITIL, or Microsoft Certified: Azure Solutions Architect Expert. • Expertise in multi-modal AI (Image-to-Text) or federal governance frameworks (e.g., EO 14110). Required Education • Bachelor's or master's in computer science, Data Science, IT, or related field. • ITIL certification • Certifications in AI/ML operations tools (e.g., Dynatrace, AppDynamics.