Work Schedule: Remote work and Flexible / as needed. Primarily evenings and weekends preferred but not required. Hours vary week to week based on project volume – some weeks multiple reviews, some weeks none. AllenComm delivers custom eLearning for enterprise clients. Our current platform testing coverage is limited to Apple devices only. We need a contractor who can test across our full device matrix – Windows PCs, Macs, tablets, and phones – to ensure deliverables perform correctly for all learners before client delivery. This is a new role to expand and eventually replace our current partial platform coverage. Job Description Summary of Duties: Test AllenComm eLearning deliverables across a defined device and browser matrix prior to client delivery. Identify and document rendering, navigation, and functionality issues specific to device or browser environment. Provide written feedback using AllenComm’s standard QC checklist. Key Responsibilities: Test across the full AllenComm device matrix: PCs (Windows 11, Chrome and Firefox), Macs (macOS 13 Ventura, Safari), Tablets (iOS 16, Safari), Phones (iOS 16 Safari and Android 14 Chrome). Document device- and browser-specific issues clearly with steps to reproduce. Complete reviews within agreed turnaround windows. Submit hours weekly. Required Skills/Qualifications: Access to and working familiarity with all devices in the AllenComm test matrix: Windows 11 PC, Mac running macOS 13 (Ventura), iOS 16 device (iPhone or iPad), and Android 14 device. Proficiency testing in Chrome, Firefox, and Safari. Ability to identify and clearly document browser- and device-specific issues. Strong written communication. Reliable availability for evening / weekend review windows. Preferred Skills/Qualifications: Experience testing Articulate Rise or Storyline output. Background in eLearning QA or development. Familiarity with responsive design and how eLearning content renders across screen sizes. Experience with proofreading and functionality testing. Comfortable working asynchronously with remote teams.

Title: Senior Platform Engineer Location: Rochester United States Full Time Remote: Yes Job Description: Why Mayo Clinic Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans - to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic. Benefits Highlights - Medical: Multiple plan options. - Dental: Delta Dental or reimbursement account for flexible coverage. - Vision: Affordable plan with national network. - Pre-Tax Savings: HSA and FSAs for eligible expenses. - Retirement: Competitive retirement package to secure your future. Responsibilities The Mayo Clinic Platform AI team is seeking an experienced Senior Platform Engineer to join our innovative efforts in developing and implementing cutting-edge generative AI solutions. In this role, you will lead the design and development of state-of-the-art generative AI models, establish comprehensive safety guardrails for responsible AI deployment, and drive the creation of autonomous AI agents. You'll collaborate closely with a diverse team of data scientists, product managers, and engineers as we shape the future of AI applications while ensuring our systems remain safe, ethical, and scalable. Key Responsibilities - Generative AI Model Development: Architect, design, and implement advanced generative AI models and architectures that support varied departmental applications and cutting-edge research initiatives. - GenAI Safety & Ethics: Develop comprehensive safety guardrails and ethical guidelines to ensure responsible AI development and deployment, incorporating best practices in AI alignment and security. - Cross-Functional Collaboration: Partner with cross-functional teams to integrate AI solutions seamlessly within the Mayo Clinic Platform, translating business needs into robust technical implementations. - Autonomous AI Agents: Lead the creation and optimization of intelligent AI agents designed for autonomous decision-making, leveraging techniques in prompt engineering and model fine-tuning. - System Enhancement: Evaluate and enhance existing generative AI deployments across departmental applications, continually iterating to improve performance, safety, and scalability. - Performance Optimization: Identify bottlenecks in AI/ML pipelines and propose solutions to improve system performance, efficiency, and scalability. - Monitoring & Troubleshooting: Develop and maintain observability tools, including logging, monitoring, and alerting, to diagnose and resolve production issues. - Documentation: Create and maintain technical documentation, including architectural diagrams, API specifications, and onboarding guides for internal and external stakeholders. - Thought Leadership: Stay updated with the latest trends and advancements in federated learning, distributed computing, and machine learning frameworks to continually enhance the platform. This vacancy is not eligible for sponsorship/ we will not sponsor or transfer visas for this position. Also, Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program Qualifications - Bachelors degree in a relevant information technology field or a minimum 7 years of direct full-stack engineering with increasing complexity. - 3-5 years working in diverse environments utilizing Agile principles of software development. - Proven experience as a Full Stack Engineer with a strong emphasis on healthcare interoperability. - Proficiency in Java and/or .NET for backend development, including API / service design and implementation. - Expertise in Javascript with a focus on React and react frameworks (e.g. NextJS) for building responsive and intuitive front-end applications. - Hands-on experience with Google Cloud Platform (GCP) (or equivalent) services and cloud-native application development. - Familiarity with healthcare interoperability standards such as HL7, FHIR and OMOP. - Strong problem-solving skills and the ability to work in a collaborative, cross-functional team environment. - Experience with DevOps practices, CI/CD pipelines, and containerization technologies (e.g., Docker, Kubernetes) is a plus. - Knowledge of healthcare data security and compliance requirements, including HIPAA, is highly desirable. - Excellent communication skills and the ability to convey complex technical concepts to non-technical stakeholders. - A proactive and self-driven mindset with a passion for staying up-to-date with emerging technologies and industry best practices. - Experience with Interoperability standards such as HL7, FHIR and OMOP. - Experience with solutions integration/delivery in a healthcare setting. Preferred Experience: - LLM Fine-Tuning: Experience in fine-tuning large language models and advanced prompt engineering techniques. - AI Alignment & Safety: Hands-on background in AI alignment strategies and the development of robust safety mechanisms. - RAG Expertise: Familiarity with Retrieval-Augmented Generation (RAG) techniques to improve model responsiveness and efficiency. - Production Deployment: Proven experience with AI model deployment and scaling in production environments, including container orchestration and cloud-based solutions. - Multi-Modal AI: Understanding and experience working with multi-modal AI systems that integrate text, image, and other data types. Exemption Status Exempt Compensation Detail $127,961.60 - $185,515.20 / year Benefits Eligible Yes Schedule Full Time Hours/Pay Period 80 Schedule Details Monday - Friday, Business Hours 100% Remote. 10%+ travel may be required. Weekend Schedule Not Applicable International Assignment No Site Description Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is. Equal Opportunity All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the 'EOE is the Law'. Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

• Provide L2/L3 support for device management solutions (Intune managed laptops) and Azure based virtual desktop environments (VDI) services, including incident diagnosis and restoration. • Manage service requests, configuration updates, and access provisioning in accordance with governance. • Execute planned changes, maintenance, and deployments; validate outcomes and document results. • Identify recurring issues; open and drive problem investigations through to permanent fixes. • Maintain and improve runbooks, monitoring, and alerting to reduce mean time to detect/resolve. • Collaborate with adjacent teams (network, identity, endpoints, security) for integrated troubleshooting. • Support service reviews by providing metrics, trend analysis, and improvement recommendations. • Ensure compliance with security, risk, and audit requirements relevant to the service set.

• As a machine learning engineer or scientist, your expertise will be pivotal in developing AI-powered solutions to shape the future of the Airbnb agentic growth platform with cutting-edge AI techniques. You will drive and guide the rest of the engineers to brainstorm, design and develop AI products and features from inception to production. • Collaborate with cross-functional leaders, build resilient systems that operate globally at scale, and help evolve the foundational building blocks behind AI-powered growth systems. • Work with large scale structured and unstructured data; explore, experiment, build and continuously improve Machine Learning models and pipelines for Airbnb product, business and operational use cases. • Work collaboratively with cross-functional partners including product managers, operations and data scientists, to identify opportunities for business impact; understand, refine, and prioritize requirements for machine learning, and drive engineering decisions. • Hands-on develop, productionize, and operate ML/AI models and pipelines at scale, including both batch and real-time use cases. • Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep. • Collaborate actively with engineers to apply ML / AI in their solutions to help validate ideas and guide to the right outcomes. • Partner with ML/AI Engineers in foundations engineering to mentor and develop initiatives that make ML/AI applications a core discipline for non-ML/AI engineers.