Note: The job is a remote job and is open to candidates in USA. Wilcore Technologies is hiring an AI/ML Engineer to support an enterprise cloud-based data and analytics platform for a federal health agency. The role focuses on delivering scalable, governed, production-ready AI/ML infrastructure, reusable modeling and generative AI patterns, operational integrations, observability, trustworthy-AI controls, and user onboarding.
Responsibilities
- 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
Skills
- Experience and expertise launching, scaling, and supporting cutting-edge AI/ML tooling is required for this role
- Expertise in the disciplines and technical areas related to the AI/ML enablement tasks described above
- 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
- 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
Company Overview