AI/ML Engineer (Contingent)

WILCORE TECHNOLOGIES INC; United States; On-site; USD 140,000 - 200,000; Full time

Job summary

Wilcore is hiring an AI/ML Engineer to support a federal health agency's cloud-based data and analytics platform. You will deliver scalable, production-ready AI/ML solutions, focusing on governance, PHI processing, and trusted-AI controls.

Responsibilities include building reusable templates for predictive modeling and NLP, integrating AI outputs into operations, and ensuring observability and cost-efficiency across pipelines. U.S. work authorization required.

Qualifications

• Experience launching, scaling, and supporting AI/ML tooling.
• Expertise in the disciplines and technical areas related to the AI/ML enablement tasks described above.

Responsibilities

• Provide AI/ML infrastructure and tooling.
• Publish reusable templates and patterns for NLP and AI.
• Integrate AI output into operations with reliable SLAs.
• Implement end-to-end observability for ML pipelines.
• Operate trustworthy-AI controls and risk assessments.

Skills

Launching and Scaling AI/ML Tooling

Relevant Disciplinary Expertise

Tools

Azure

Job description

Wilcore is hiring an AI/ML Engineer to support an enterprise cloud-based data and analytics platform for a federal health agency. The platform provides governed data storage, engineering and analytics tools, platform integrations, and policy controls for data practitioners across the enterprise, and supports advanced use cases including data science, machine learning, and artificial intelligence.

In this role you will deliver scalable, governed, production-ready AI/ML on the platform, standardizing reusable patterns for predictive modeling, natural language processing, and generative AI, supporting structured and unstructured data, and meeting the agency's trustworthy‑AI requirements.

Contract Contingency Notice:This position is contingent upon contract award. Employment offers will be extended only upon successful contract award and client approval. Candidates may be considered and interviewed in advance to support rapid onboarding should the contract be awarded.

What you'll be doing:

• Provide AI/ML Infrastructure and Tooling: Deliver scalable AI/ML infrastructure and tooling leveraging the platform's tool stack, aligned with architecture guidelines, source control, CI/CD, and tagging conventions.
• Publish Reusable Templates and Patterns: Build a reusable pattern and template library covering predictive modeling — feature pipelines, training and validation, model registry — NLP and text analytics including clinical and operational free-text note analysis and PHI processing, and generative AI including prompt orchestration, guardrails, content filters, and human-in-the-loop workflows.
• Integrate AI Output into Operations: Integrate AI output into operations for use cases related to clinical decision support, risk prediction, operational analytics, and similar applications, using standard interfaces and reliability SLAs.
• Implement End-to-End Observability: Implement observability for ML pipelines covering data lineage, experiment tracking, model monitoring for quality, drift, and bias, and alerts routed to the platform's monitoring stack.
• Operate Trustworthy-AI Controls: Operate controls around privacy, safety, fairness, and transparency, maintaining risk assessments and audit evidence for high-impact use cases.
• Optimize Cost and Performance: Optimize cloud cost and performance for training and serving through autoscaling, job parallelism, caching, and partitioning, and report efficiency gains quarterly in an AI/ML Health Report.
• Operate Onboarding and Upgrade Processes: Stand up and operate AI/ML onboarding and upgrade processes that educate workgroups about the newest AI/ML tooling versions, and onboard users to AI/ML tools and features in alignment with platform provisioning and architecture patterns.
• Coordinate Across Workstreams: Coordinate with engineering and governance workstreams so AI/ML workloads leverage shared ingestion frameworks, catalog metadata and taxonomy, and common monitoring and alerting for repeatable, production-grade operations.
• Run Discovery and Pilots: Conduct discovery, prioritize intake, and run pilots for selected high-potential, early-stage AI concepts. Provide hands-on support in shared compute resources, including environment setup, model development assistance, and technical troubleshooting.
• Build Frameworks and Playbooks: Design frameworks, runbooks, and standardized KPIs to measure success and support future iterations, develop decision-readiness materials, and create a reusable pilot-design playbook for future innovation cycles.

What you'll bring:

• Launching and Scaling AI/ML Tooling: Experience and expertise launching, scaling, and supporting cutting-edge AI/ML tooling is required for this role.
• Relevant Disciplinary Expertise: Expertise in the disciplines and technical areas related to the AI/ML enablement tasks described above.

Bonus if you have:

• Experience launching, scaling, and supporting AI/ML tooling in an Azure environment
• Direct experience deploying AI/ML or data science solutions at a federal agency

Requirements:

• Applicants must be authorized to work in the United States.
• Must be able to obtain and maintain a federal Public Trust (Tier 2 / Moderate Risk) background investigation.
• Must reside and perform all work within the continental United States.
• Production system monitoring and support coverage runs 7:00 a.m. to 8:00 p.m. Eastern Time, with participation in a 24/7 on‑call escalation process for urgent issues.
• This position is contingent upon contract award.