We run member and prospect outreach for Medicare Advantage clients. The full system already works: ingest, identity, scoring, audience build, vendor file, matchback. We are not rebuilding it. One module is the problem. Eligibility, suppression, and release checks still depend on a large Excel workbook. The Databricks job that consumes those rules is in production. After a recent Snowflake permission change it has been failing, and even when it succeeds we do not fully trust the file. A wrong include or a missed suppression is a compliance issue, not a metric miss. PHI leaves the building. We need a senior engineer who can treat this as a system repair, not a notebook exercise. Read the live PySpark / SQL job. Trace the workbook into executable rules. Use an LLM only to accelerate extraction and to draft QC, then verify every rule against source tables before anything is trusted. Write the checks that catch duplicates, bad exclusions, test/control leakage, and count breaks before release. This is data engineering with model-assisted rule work. If your background is only model fitting, this is not the right job. If you have shipped person-level pipelines and can keep an LLM from inventing a business rule, it is. Stack on this module: Databricks, PySpark, Snowflake, SQL, Python. Git, AWS, SFTP, and Linux show up around the job. Excel is the current spec. US-based only. Background check, OIG screen, HIPAA training, and a BAA are required before data access.

Principal AI Infrastructure & HPC Engineer We are a PE-backed, AI-native technology services company building a new AI Infrastructure & HPC practice across AWS and Microsoft Azure. We're looking for a deeply technical engineer to help build the practice from the ground up. This is not a traditional cloud or DevOps role. The focus is large-scale GPU infrastructure, distributed AI workloads, high-performance networking, and getting expensive compute environments to perform at their potential. What You'll Work On GPU cluster benchmarking, performance tuning and optimization NCCL benchmarking and tuning AWS EFA and Azure GPU/HPC infrastructure InfiniBand, RDMA, RoCE and GPUDirect RDMA CUDA, NVLink/NVSwitch and NVIDIA GPU environments Distributed AI training and inference optimization Linux, kernel, driver and systems-level performance Kubernetes/EKS/AKS and Slurm-based GPU environments GPU cloud / neocloud infrastructure What We're Looking For We want someone with deep hands-on expertise in GPU/HPC systems who can benchmark an environment, identify where performance is being lost, and fix it. Experience with NCCL, CUDA, InfiniBand/RDMA, distributed training, Linux performance engineering, and large multi-node GPU clusters is particularly relevant. Deep AWS and/or Microsoft Azure experience is a major plus, particularly experience designing or optimizing GPU/HPC workloads using EFA, EC2 accelerated computing, Azure GPU infrastructure, EKS/AKS, and high-performance networking. You don't need to check every box. Depth in this domain matters more than breadth. More Than a Project We're building a practice around this capability. The right person can play an important role in defining our technical offerings, developing repeatable optimization methodologies, working directly with AWS and Microsoft, and helping us build the engineering team as the practice grows. If you've worked deep in GPU infrastructure, HPC, distributed systems, or high-performance networking, we'd like to talk.

MNT AI USA Suite 210, 1555 Naperville Wheaton Road, Naperville, IL 60563 AI Associate Instructor Location: Naperville, IL (in-person, Suite 210) | Job Type: Full-Time MNT AI USA is looking for an AI Associate Instructor to join our Naperville team and help small businesses put AI to work. In this role, you'll teach practical, hands-on training on today's leading AI tools and guide business owners through real implementation, not just theory. If you love using AI tools daily, explaining them clearly, and watching a room have that "aha" moment, we want to talk to you. What You'll Do • Deliver in-person training sessions and workshops for small business owners and their teams on how to use AI tools effectively in day-to-day operations. • Teach both the theory (how these tools work and when to use them) and the practical, hands-on application (how to actually implement them for a real business need). • Build customized curriculum, demos, and exercises tailored to different industries and business use cases. • Work hands-on with tools including Claude, ChatGPT, Perplexity, Design Arena, Replit, Notebook LLM, Base44, and similar AI platforms. • Help clients identify practical, value-adding AI use cases for their business, from content and research to automation and workflow tools. • Stay current on new AI tools, features, and best practices, and continuously update training materials accordingly. • Answer client questions, troubleshoot tool issues, and provide ongoing support as needed. • Collaborate with the MNT AI USA team, including the Entry-Level AI Instructor, to refine training programs based on client feedback and outcomes. What We're Looking For • Prior hands-on experience with AI tools is required. You should already be comfortable using platforms like Claude, ChatGPT, Perplexity, Replit, and similar tools in real projects. • Prior knowledge of AI concepts and applications is required; this is not an entry-level introduction to AI. • Strong communication and presentation skills. You can explain technical concepts in plain language to non-technical audiences. • A teaching, training, or coaching background is a plus, but a genuine passion for helping others learn matters just as much. • Comfortable working in person at our Naperville office and leading live sessions. • Self-starter who can build and adapt training content independently. • Business or consulting mindset, able to translate AI capabilities into practical value for small businesses. Application Requirement As part of the interview process, candidates must be prepared to present a business case they personally built using AI tools. During the technical round, you'll be asked to walk us through what you created, which tools you used, and the value it delivered. Why Join MNT AI USA • Be part of a growing company at the forefront of helping small businesses adopt AI. • Work directly with business owners and see the real-world impact of your training. • Collaborative, in-person team environment in Naperville, IL. How to Apply Submit your resume along with a brief note on your experience with AI tools. Be ready to demonstrate your AI-built business case during the technical interview.

# AI Business Tools Trainer and Consultant for Healthcare/DME Company ## Project Overview Hiro Health is a growing healthcare company specializing in sleep diagnostics, CPAP therapy, PAP resupply, oxygen services, ventilator services, and durable medical equipment. We are seeking an experienced AI business trainer and consultant to provide personalized, hands-on instruction to the company owner and selected managers. The goal is to teach us how to effectively use AI platforms such as: * ChatGPT * Claude * Google Gemini * Microsoft Copilot * Other relevant AI and automation tools This is not a general introductory AI course. Training must be customized around Hiro Health’s actual business operations, financial reporting, healthcare research, management responsibilities, and growth plans. ## Primary Objective At the completion of the project, we should be able to independently use AI to: * Analyze business and financial information * Improve operational processes * create reports, policies, and procedures * Conduct reliable business and healthcare research * Develop employee and management materials * Evaluate acquisitions and growth opportunities * Identify tasks that can be automated * Select the best AI platform for each type of project * Protect confidential patient, employee, and company information The consultant should teach us how to use AI—not simply perform the work on our behalf. ## Areas of Training ### 1. AI Platform Selection Teach us the differences between ChatGPT, Claude, Gemini, and Microsoft Copilot, including: * Strengths and weaknesses of each platform * Best business uses for each tool * Free, paid, business, and enterprise account differences * File-upload and data-analysis capabilities * Research and source-verification capabilities * Integration with Microsoft 365, Google Workspace, and other systems * Privacy and data-retention considerations ### 2. Prompt Development Teach us how to: * Write clear and effective prompts * Provide the appropriate background, data, and instructions * Improve an AI-generated answer through follow-up prompts * Create reusable prompt templates * Build multi-step prompts for complex projects * Reduce inaccurate or fabricated responses * Verify important facts and calculations * Convert successful prompts into standardized company workflows ### 3. Financial Analysis Use realistic Hiro Health examples to teach AI-assisted: * Profit-and-loss statement analysis * Balance-sheet and cash-flow analysis * Budget development * Financial forecasting * Gross-margin analysis by service line * Labor and productivity analysis * KPI development and reporting * 13-week cash-flow forecasting * Acquisition valuation and financial modeling * SBA loan and debt-service analysis * Excel formula, table, dashboard, and chart creation * Comparison of actual results against budgets and benchmarks ### 4. Operations and Process Improvement Teach us how to use AI to: * Create and improve standard operating procedures * Document departmental workflows * Identify process bottlenecks * Develop quality-control checklists * Build employee training materials * Analyze operational reports * Create management dashboards * Develop implementation and project plans * Improve CPAP setup, resupply, sleep-testing, oxygen, and ventilator workflows * Identify repetitive tasks that may be automated ### 5. Sales and Referral Management Training should include: * Physician-referral data analysis * Referral-source ranking and segmentation * Sales-territory analysis * Identification of declining or underperforming accounts * Sales representative performance analysis * Sales plans and account strategies * Physician outreach emails and materials * Competitor and market research * Commission and incentive-plan modeling * Customer-review and satisfaction analysis ### 6. Human Resources and Management Teach us how to use AI to develop: * Job descriptions * Interview questions * Candidate scorecards * Performance evaluations * Employee policies * Corrective-action plans * Training documents * Internal company communications * Meeting agendas and summaries * Organizational and staffing plans * Compensation comparisons * Employee productivity measurements ### 7. Healthcare, DME, and Reimbursement Research Teach us how to conduct and verify research involving: * Medicare and commercial insurance requirements * DME billing and reimbursement * HCPCS and CPT codes * CPAP, oxygen, ventilator, and sleep-testing requirements * Industry benchmarks * Market and competitor information * Accreditation and licensing requirements * New product and service opportunities * Authoritative government and payer sources The trainer should emphasize that AI research does not replace legal, clinical, billing, compliance, or accounting review. ### 8. AI Automation Opportunities Teach us how to identify and evaluate opportunities involving: * Microsoft Copilot * Microsoft Power Automate * AI agents * Robotic process automation * Scheduled reports * Automated document summaries * Email and meeting follow-up * Data extraction and classification * Management notifications * Brightree, QuickBooks, Microsoft Fabric, Shopify, and Microsoft 365 workflows The consultant should explain when generative AI is appropriate and when traditional automation or systems integration is a better solution. ## Healthcare Privacy and Security Because Hiro Health operates in healthcare, the training must address: * HIPAA and protected health information * Personally identifiable information * De-identifying information before using AI * Consumer versus enterprise AI accounts * Business Associate Agreement requirements * Data-retention and model-training settings * User access and permission controls * Approved and prohibited AI uses * Review requirements before AI-generated work is used * Situations in which information should never be entered into an AI platform Actual patient information should not be used during training. Examples should rely on synthetic, anonymized, or properly de-identified information. ## Preferred Project Structure We anticipate a six-to-eight-week engagement consisting of: * One or two virtual training sessions per week * Approximately 60–90 minutes per session * Hands-on exercises using Hiro Health business scenarios * Assignments between sessions * Recordings of sessions when permitted * Reusable templates and reference materials * Limited follow-up support between sessions * A final AI implementation plan We are open to an alternative structure if the consultant recommends a more effective approach. ## Required Deliverables The consultant should provide: 1. An initial assessment of our AI knowledge and business priorities. 2. A customized training curriculum. 3. Live, hands-on training sessions. 4. A comparison guide for ChatGPT, Claude, Gemini, and Microsoft Copilot. 5. A reusable prompt library organized by business function. 6. At least five completed AI-assisted workflows based on Hiro Health’s needs. 7. Step-by-step instructions for each workflow. 8. An AI privacy, security, and acceptable-use checklist. 9. A process for verifying AI-generated work. 10. Recommendations for appropriate business or enterprise AI subscriptions. 11. A prioritized list of future automation opportunities. 12. A 90-day AI implementation roadmap. ## Ideal Candidate The ideal consultant will have: * Advanced experience with ChatGPT, Claude, Gemini, and Microsoft Copilot * Experience teaching business owners and executives * Strong prompt-engineering and workflow-design skills * Experience with Excel and Microsoft 365 * Business financial-analysis experience * Knowledge of AI privacy, security, and governance * The ability to explain technical topics in straightforward business language * Experience converting AI use cases into repeatable company processes Healthcare, DME, HIPAA, Brightree, QuickBooks, Microsoft Fabric, or Power Automate experience is strongly preferred. ## Proposal Requirements Please include: * A summary of your relevant experience * Examples of similar AI training engagements * Your experience with healthcare or regulated businesses * Your proposed training structure * Estimated project timeline * Hourly rate or fixed project price * Examples of training materials or workflows you have created * Relevant AI, Microsoft, healthcare, or technology certifications * Your availability for live virtual sessions ## Applicant Screening Questions 1. How would you compare ChatGPT, Claude, Gemini, and Microsoft Copilot for a healthcare business? 2. What precautions should a HIPAA-regulated company take when using AI? 3. Describe a business workflow you have improved using generative AI. 4. How do you teach users to recognize incorrect or fabricated AI answers? 5. How would you structure a customized AI training program for Hiro Health? 6. What experience do you have using AI with Excel, financial statements, and operational data? 7. How would you help us build a reusable company prompt library? 8. What healthcare, DME, Microsoft 365, or automation experience do you have? ## Definition of Project Success At the conclusion of the project, Hiro Health’s owner and participating managers should be able to: * Select the appropriate AI tool for a specific business need * Write effective prompts without outside assistance * Analyze common company reports and spreadsheets * Create professional business documents * Conduct and verify business research * Protect confidential and regulated information * Develop reusable prompts and AI workflows * Identify strong candidates for automation * Train additional employees on approved AI practices * Continue developing AI-assisted workflows independently

Background - manufacturing engineering and AI company We're building a curriculum teaching the first-principles of AI in manufacturing and engineering automation to a mix of existing plant operators and software engineers with EE/ME backgrounds You should love reducing complex systems to their essential components - we're open to people from a range of backgrounds: AI systems, MES engineering, robotics automation, CNC integration

NobleProg is seeking an experienced AI Trainer to deliver a live, instructor-led workshop for a corporate client in the Irvine, California area. This four-hour workshop is designed primarily for the client’s Quality team, with invited participants from Pharmaceutical Sciences, Innovation Labs, and Clinical. The trainer should have strong expertise in enterprise generative AI and practical experience applying AI within pharmaceutical and life sciences organizations. The objective is to help AI Champions and business users identify meaningful opportunities to expand the responsible use of AI across regulated business functions. Engagement Details Location: Irvine, CA Duration: 4-hour workshop (9:00 AM – 1:00 PM) Audience: Quality team, with invited participants from Pharmaceutical Sciences, Innovation Labs, and Clinical Participants: Approximately 25 Format: Onsite + Remote Participants Rate: $750 Course Scope This interactive workshop introduces practical applications of generative AI across pharmaceutical quality, product development, clinical, and innovation functions. Participants will learn prompt engineering techniques, responsible AI practices, and practical business use cases while working within Microsoft Copilot and Enterprise ChatGPT. All exercises will use fictional or sanitized examples appropriate for a regulated pharmaceutical environment. NobleProg SOP: https://share.synthesia.io/a0788c6e-56d5-4da8-92c6-0d5c03ad6d52 Key Topics Include * Practical applications of generative AI in pharmaceutical product development, including research support, summarizing background information, comparing options, and planning early-stage activities * AI-assisted clinical patient screening using fictional scenarios to structure eligibility criteria, summarize screening considerations, and develop review checklists while maintaining human oversight * AI for quality and compliance workflows, including drafting review checklists, summarizing procedures, identifying documentation gaps, and improving internal quality documentation * Cross-department AI use cases supporting Pharmaceutical Sciences, Innovation Labs, Clinical, and Quality teams through meeting preparation, project planning, reporting, knowledge management, and process improvement * Prompt engineering techniques for producing reliable, structured, and business-ready outputs * Responsible AI practices, data privacy, governance, and compliance considerations in pharmaceutical environments * Strategies for AI Champions to identify, evaluate, and promote practical AI opportunities across their teams Trainer Responsibilities * Deliver an engaging instructor-led workshop for approximately 25 participants * Facilitate hands-on exercises using Microsoft Copilot and Enterprise ChatGPT * Demonstrate practical AI use cases relevant to pharmaceutical quality, clinical, research, and innovation teams * Lead discussions on responsible AI adoption, governance, and human oversight * Coach participants on prompt development, prompt refinement, and evaluating AI-generated outputs * Encourage participants to identify AI opportunities within their own business functions * Provide training materials (trainer retains ownership of content) Required Qualifications * Strong hands-on experience using enterprise generative AI platforms, particularly Microsoft Copilot and ChatGPT * Demonstrated experience applying AI within pharmaceutical, biotechnology, healthcare, or life sciences organizations * Strong understanding of AI applications supporting Quality, Pharmaceutical Sciences, Clinical, Innovation, Regulatory, Manufacturing, or related pharmaceutical functions * Experience delivering instructor-led corporate AI workshops or executive education * Excellent presentation and facilitation skills with mixed-experience audiences How to Apply Please include: * A brief overview of your AI and pharmaceutical or life sciences experience * Your experience delivering corporate AI workshops or executive education * Examples of AI use cases you have implemented or taught for Quality, Clinical, Pharmaceutical Sciences, or Innovation teams * Confirmation of your availability to deliver onsite training near Irvine, California on Tuesday, September 8 * Any relevant presentations, publications, or previous AI training materials

I’m looking for an AI Engineer to help build an AI Safety Evaluation & Governance product powered by open-source models. This is a 1-month, hands-on project with an expected commitment of around 20 hours per week. The goal is to build an MVP that can automatically test AI models, identify safety failures, analyze failure patterns, and support continuous improvement. 🔍 What you’ll work on • Build an automated red-teaming engine that generates test cases across risk domains, severity levels, and attack strategies • Run tests against models such as Gemma, Llama, Qwen, and API-based models • Develop evaluators for jailbreak success, policy violations, over-refusal, under-refusal, and severity • Structure safety policies into consistent taxonomies and evaluation criteria • Turn confirmed failures into reusable eval datasets and regression tests • Build lightweight reporting for model comparison, human review, and policy-version tracking 🧠 What I’m looking for • Experience with open-source LLMs, inference pipelines, prompt optimization, fine-tuning, LoRA/QLoRA, and LLM evaluation • Ability to independently build an end-to-end MVP, including data pipelines, model orchestration, scoring, and reporting • Familiarity with AI safety, red teaming, jailbreaks, content moderation, or Trust & Safety systems • Bonus: experience with model-based evaluators, human-in-the-loop review, agentic testing, or multimodal safety ⏳ Project setup Duration: 1 month Time commitment: Around 20 hours per week Format: Flexible and remote-friendly Stage: Early-stage, 0-to-1 MVP This is not about manually writing red-team prompts one by one. The goal is to build a scalable system that can continuously generate tests, evaluate model behavior, identify safety gaps, and verify whether issues have been resolved. If this sounds like you, please DM me with a brief introduction and examples of relevant work.

We need a lightweight, reliable Python script/tool that ingests multi-page PDF medical records, uses an LLM API (OpenAI, Claude, or Gemini) to extract structured clinical events, deterministically sorts them chronologically, and outputs a formatted Markdown/Word narrative report with page-level citations. Key Deliverables: -PDF parsing and text/OCR handling (handling digital exports and scanned records). -LLM integration using structured output (JSON schema) with prompt engineering for medical accuracy. -Python-based chronological sorting and deduplication. -Export engine generating clean .docx or .md reports. -A simple user interface (e.g., Streamlit desktop app or local command-line script) so a non-technical user can drop in a PDF and click "Generate". -Clear setup instructions and 30 days of troubleshooting support. Required Skills: -Strong Python (PDF libraries like PyMuPDF/pdfplumber, pydantic, Streamlit). -Experience with LLM APIs (Anthropic, OpenAI, or Google Cloud Vertex AI) and structured JSON outputs. -Familiarity with healthcare data handling best practices (HIPAA/security awareness).

I’m looking for a developer to help build a lightweight AI prototype using OpenAI or Anthropic APIs. This is NOT a full product build. This is a focused prototype to test a specific idea. Project Goal: Build a simple Python-based system that: Runs the same LLM task multiple times. Captures outputs and any intermediate state (memory/logs). Compares differences between runs. Classifies differences into simple categories: Stable Boundary Violation What This Means Think: •Run the same prompt 5–10 times. •Log results. •Detect where outputs or stored data differ. •Label those differences. That is it. Technical Requirements Must have: •Python •Experience with OpenAI API or Anthropic API •Ability to build simple, clean scripts (no over-engineering) Nice to have: •LangChain or similar frameworks. •Streamlit (for simple UI/dashboard). •Experience with logging or comparing outputs. Important Constraints This should be: •Lightweight. •fast to build. •easy to understand. Please DO NOT: •Design complex architectures. •build full systems. •over-engineer. Deliverables •Python script or small app. •Ability to run repeated LLM tasks. •Stored logs of runs (JSON or similar). •Basic comparison logic between runs. •Simple classification output. Timeline •3–7 days initial build •Max 1–2 weeks total Engagement Style •Fixed-price or hourly (open to discussion) •Will start with a small paid test task before full project Screening Question (Required) Please answer this: If you needed to run the same LLM task multiple times and compare outputs/state between runs, how would you build it quickly? Who This Is For Ideal candidate: •Builds fast prototypes. •Comfortable with LLM APIs. •Prefers simple solutions over complex systems.

We are a research group at Stanford University studying human workflows. We are seeking a freelance Software Engineers (SWEs). Data Scientists, AI Specialists, and Forward Deployed Engineers (FDEs) who commonly use AI tools for coding. The project involves completing a coding task or data analysis task(s) (~1 hr each) while using an open-source recording tool to capture your computer-use activities. If you have experience with completing coding projects with Claude Code or Codex and are comfortable using recording software, we encourage you to apply. Please briefly describe which of these two common AI tools that you would use for the task.