We are seeking a Mid to Senior-level Fullstack Developer (3–5 years of experience) to not only maintain and expand our platform (Next.js frontend + Django backend) but also guide us in fully integrating AI-powered coding assistance across the full stack. The frontend is already set up for AI-assisted editing (e.g. Cursor), and we want to evolve our backend similarly. The ideal candidate will help us transition the entire development environment, so both we and the developer can leverage state-of-the-art AI coding tools. Beyond coding, you’ll act as a mentor, helping us better understand the backend’s architecture and workflows while integrating AI-driven development tools into our process. You’ll have a key role in making our stack both stable and future-ready, with AI-assisted flexibility. The Context Our frontend was recently ported to Next.js in an ad-hoc manner, leaving certain sections in need of refactoring and stabilization. We have committed to keeping our backend in Django to leverage its robust processing capabilities. You will be the point person for bridging these two environments. Key Responsibilities -Maintenance & Stability: Perform routine maintenance and optimization across the full stack. -Bug Fixing: Identify and resolve issues within the existing Next.js frontend and Django backend. -System Reliability: Provide technical support and troubleshooting during system downtime. -Feature Implementation: Build and deploy new features, ensuring seamless integration between the AI pipeline and the user interface. Required Technical Profile -3–5 years of professional fullstack experience. -Frontend: Proficiency in Next.js and React; experience cleaning up/refactoring "messy" or legacy codebases is a plus. -Backend: Strong experience with Django (Python), specifically working with complex data pipelines or API integrations. -Mindset: A pragmatic approach to coding—balancing the need for new features with the necessity of technical debt reduction.

"We're migrating Fresh Start Now's core operations from Salesforce to a custom, on-premises platform. We need an experienced full-stack developer to build a secure web application that serves our nationwide bankruptcy automotive marketing business. Requirements: You'll design and build a database-backed website using SQL, HTML, and backend languages of your choice. The system must handle credit application intake, store up to thirty thousand applications with full search and retrieval, manage three hundred dealer files, and support multi-state user access with secure login authentication. You'll integrate third-party APIs including Zapier and Twilio for workflow automation and SMS notifications. The entire platform runs on our on-premises server with zero cloud dependency—you'll work with us on server architecture and deployment. We've already worked with Claude AI to design this system and have come very close in just one week. However, we lack the security expertise to ensure the platform is hardened against threats and vulnerabilities. You should have demonstrated experience with relational databases, API integrations, user authentication, secure coding practices, and building data-intensive applications that handle sensitive financial data.

Build scalable technical capabilities that support governance automation, data readiness, and AI Business Use Cases enablement Implement metadata-driven workflows, Databricks integrations, quality/scorecard pipelines, access patterns, and reusable platform services Partner with governance data engineering, security and UX teams to ensure solutions are secure, maintainable, automated and repeatable across BU’s

Hello, I'm looking for an experienced automation engineer or systems integrator to build a cloud-based automated messaging system for our restaurant operations. We operate 10 restaurant locations with approximately 40 Motorola TLK 25 radios using WAVE PTX. The goal is to use Radio.co to schedule already created operational voice mp3 reminders (opening procedures, food safety checks, labor reviews, closing tasks, etc.) and automatically broadcast those messages to designated WAVE PTX talk groups. The proposed solution would utilize: * Radio.co for scheduling and audio content * Azure Windows VM as a dedicated cloud-hosted dispatch workstation * WAVE PTX Dispatch for radio communications * Virtual audio routing and PTT automation to transmit scheduled messages to Motorola TLK 25 devices We're looking for someone who can design, deploy, test, and document the complete solution, including Azure configuration, audio routing, automation, monitoring, and scalability for future growth. If you have experience with cloud infrastructure, automation, streaming audio, dispatch systems, or Motorola WAVE PTX, please let me know how you would approach this project. We have a clear vision and proposed architecture for this project and are looking for a skilled developer to help execute, validate, and deploy it. The objective is to create a cloud-based automated messaging system that uses Radio.co for scheduled voice reminders and broadcasts those messages to Motorola TLK 25 radios through WAVE PTX Dispatch. We anticipate utilizing an Azure Windows VM, virtual audio routing, and automated Push-to-Talk activation to create a reliable, scalable solution for restaurant operations. At this stage, we need a technical expert who can review our proposed workflow, identify any improvements or challenges, and then build, test, document, and deploy the solution. The ideal candidate has experience with cloud infrastructure, automation, audio streaming, browser automation, dispatch systems, or Motorola WAVE PTX. We value practical execution and problem-solving and are looking for someone who can take an existing concept and turn it into a production-ready system.

We are seeking an experienced Bubble.io developer to help build, maintain, and enhance web applications on an ongoing basis. The ideal candidate has a strong portfolio of Bubble projects, experience with API integrations, database architecture, workflow optimization, and responsive design. We prefer candidates located on the East Coast of the United States to facilitate collaboration during business hours. Strong communication skills, reliability, and the ability to work independently are essential. Please include examples of Bubble applications you've built and describe your role in each project. To confirm you've read this posting, please begin your proposal with the phrase "Bubble Builder" and include links to your Bubble portfolio. The selected contractor must be willing to sign a Confidentiality, Intellectual Property Assignment, and Non-Use Agreement before engagement. This agreement includes provisions regarding confidentiality, ownership of all work product and intellectual property, protection of proprietary technology and business processes, and restrictions on the use or disclosure of confidential information.

We're hiring 2 experienced developers to build AIOS deployments for our growing client base. FluentOS is a 9-person team that builds AIOS (AI operating systems) that connect a business's existing platforms together and run AI agents on top of them. We're onboarding 6–7 new client projects every week and need two more builders who can take a project and deliver it. The industries we work in: We deploy across a wide range of professional and service businesses, so you'll get variety: - Financial services & wealth advisory - Tax & accounting firms - Dental and medical practices - Home services & roofing - Property management Each client runs on a different stack — CRMs, comms tools, scheduling, payment systems, document and data sources — and our job is to unify those into one system and build agents that operate across them (lead response, follow-up, reporting, document workflows, estimating, intake, and more). What you'd be building: - AIOS deployments end to end — integrating client platforms via their APIs - AI agents that read/write across those connected systems - Reliable, production-grade automations that real businesses depend on daily What we're looking for: - Proven delivery experience — you've shipped projects clients actually use, not just personal experiments - Strong coding background (Python and/or TypeScript); comfortable with API integrations and agent frameworks - Experience with LLM/agent development (Anthropic/Claude, tool use, multi-step agents) is a big plus - Fast, organized, and communicative — we move quickly and build as a team, not in isolation - Able to work closely with Ray, our lead developer, who'll get you ramped into live projects The setup: - 1099 contract, paid per project — not salaried - Steady, scalable volume (6–7 new projects/week) means consistent work for builders who deliver - Strong potential for ongoing, long-term collaboration as we scale To apply: Tell us briefly about a real project you've built and delivered — ideally something involving API integrations, automation, or AI agents. Include links to work or repos if you have them. Please start your reply with the word "FLUENT" so we know you read this. We'll be scheduling interviews shortly.

We've built an AI tool that reads a full lab panel and drafts a structured clinical analysis (patterns, HOMA-IR, biological age) for the physician to review, edit, and sign. Before launch, we want a practicing functional/integrative MD or DO to evaluate it on two axes: 1) Clinical accuracy — are the detected patterns, severities, and derived metrics correct? Where does it over- or under-call? 2) Usability — does the workflow fit a real functional-medicine practice? What would block adoption? Engagement: ~6–10 hours of work · fully remote · paid (share your rate). Important: all work on synthetic / de-identified data — no real patient information. NDA before access. You get: a test account, ~8–10 synthetic case panels, a scoring template, a one-page orientation. Deliverable: completed scoring sheets + a 2–4 page written evaluation. Nice to have: IFM / A4M / ACAM / Bastyr training. This is an evaluation of software — not the provision of care, and not human-subjects research.

We're hiring a senior AI developer to build and deploy AI solutions for a fintech/credit-union platform. The work spans autonomous banking agents, fraud detection, credit scoring, and bill-pay/invoice automation — at the intersection of LLMs, cloud infrastructure, and financial-domain expertise, with security and compliance built in from the start. This is a long-term, ongoing engagement. What you'll do: AI agents & orchestration - Design, build, and deploy multi-agent systems using Amazon Bedrock Agents, LangChain, and related frameworks - Architect agentic workflows for core banking use cases: credit scoring, fraud detection, bill-pay automation, invoice management - Define agent personas, memory strategies, tool-use patterns, and escalation paths for production banking agents LLM engineering - Fine-tune, prompt-engineer, and evaluate LLMs for financial-domain tasks - Build RAG pipelines over credit-union knowledge bases, policy docs, and member data - Implement guardrails, content filtering, and compliance checks for safe, regulated outputs - Monitor performance, hallucination rates, and latency against SLAs Cloud infrastructure (AWS & Azure) - Architect and manage AI/ML workloads on AWS (Bedrock, SageMaker, Lambda, S3, IAM, VPC) and Azure (OpenAI Service, Azure ML, AKS) - Design secure, cost-optimized environments compliant with NCUA, PCI-DSS, and SOC 2 - Implement infrastructure-as-code with Terraform or AWS CDK DevOps & MLOps - Build and maintain CI/CD pipelines (GitHub Actions, Jenkins, CodePipeline, Azure DevOps) - Containerize services with Docker, orchestrate with Kubernetes (EKS/AKS) - Apply MLOps best practices: model versioning, A/B testing, canary deployments, automated rollback - Stand up observability with logging, tracing, and alerting Python development - Write clean, well-tested Python for AI pipelines, REST APIs, and data workflows - Build FastAPI/Flask microservices exposing agent capabilities to frontend and core banking systems - Integrate with financial data sources, core banking APIs, and third-party fintech services Banking applications - Build credit-scoring models using alternative data and explainable AI (XAI) - Develop real-time fraud detection with behavioral analytics, anomaly detection, and auto-decisioning - Create conversational agents for bill pay, account management, and member self-service - Automate invoice workflows: extraction, classification, approval routing, reconciliation - Partner with compliance/risk to keep AI decisions auditable, fair, and regulatory-compliant What you should have: - 5+ years software engineering; 3+ years in AI/ML or LLM engineering - 2+ years building AI for banking, credit unions, or financial services - Hands-on experience with Amazon Bedrock, LangChain, Python, AWS, and infrastructure-as-code - Working knowledge of NCUA, PCI-DSS, SOC 2, GLBA, and Fair Lending requirements - Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or related field Nice to have: - AWS or Azure AI/ML certifications - Open-source LLM experience (Llama, Mistral, Phi) and self-hosted inference (vLLM, Ollama) - Vector databases (Pinecone, OpenSearch, pgvector) - Graph-based fraud networks and graph ML - AI governance / responsible AI framework experience - Prior work at a credit union, community bank, or fintech lending platform To apply, please share: - Your resume highlighting AI and banking project experience - A brief note on your most impactful AI agent or LLM project in a financial-services context - Links to GitHub, portfolio, or published papers (optional but encouraged)

### Responsibilities: The selected candidate(s) will collaborate with our content creators and advisors to produce 20 to 40 polished videos within approximately four weeks. Key features of our video service include: - **Audio/Video Correction**: Ensuring clear sound and visuals. - **Ambient Noise Removal**: Eliminating background noise for professional audio. - **Lighting & Color Correction**: Enhancing visual quality through adjustments. - **Motion Graphics**: Creating engaging graphics to illustrate concepts. - **Lower Thirds Annotations**: Adding informative text overlays. - **Teaching Annotations**: Enhancing learning with educational notes. - **Brolls**: Including imagery from provided materials and stock footage. - **Transition Effects**: Incorporating smooth transitions. - **Music Integration**: Adding music to enhance content. - **Brand Matching**: Integrating logos and branding elements seamlessly. ### Requirements: - Proven experience in editing eLearning and "talking-head" videos. - Proficiency in video editing software (e.g., Adobe Premiere Pro, Final Cut Pro). - Strong understanding of video production workflow and ability to meet deadlines. - Excellent attention to detail and creative problem-solving skills. - Strong communication and collaboration abilities. ### AI Software to Utilize: - Veed.io (http://veed.io) - Spikes Studio (https://www.spikes.studio) - Pixop (https://www.pixop.com) - Heygen (https://www.heygen.com) - Guidde (https://www.guidde.com) ### Benefits: - Projects typically involve editing 20 to 60 videos for large courses. - Opportunities to complete animation promotion videos. - Project-based pay for each completed video. - Work with a dynamic and innovative team. - Flexibility to work remotely or on-site as needed. - Guaranteed ongoing collaboration on future projects. ### How to Apply: Interested candidates should send a detailed resume, portfolio with relevant work, and a cover letter explaining their fit for this role. Please include "Video Editor Application" in the subject line and provide examples of editing "talking-head" or lecture content from course creators. Join us in revolutionizing the eLearning industry—apply today! See our video editing sales PDF to gain more insights.

I am looking for an experienced ASR engineer to build a production-ready speech-to-text system for a low-resource language. I already have approximately 3,000 prepared audio segments, totaling about 10 hours of audio, with clean and consistent transcripts ready for immediate use. Data preparation and segmentation are already handled. The initial 10 hours of audio will serve as the first milestone. After that, the engineer will be expected to continue training and improving the model with additional data until the system reaches a target WER of 10% or below. Your responsibility will focus on: Fine-tuning a Whisper-based model for high transcription accuracy Optimizing word error rate (WER) over time Providing inline/embedded start timestamps per phrase Building an efficient inference pipeline for both real-time and batch transcription Structuring evaluation and improvement workflows Preparing the system for deployment and integration into a web platform Providing clear documentation and guidance so I can independently continue training and improving the model over time without ongoing engineer involvement The goal is to reach strong accuracy at launch, with a clear process for continued improvement as more data becomes available. Please describe your experience with Whisper fine-tuning or similar ASR model training in your proposal.