We are looking for an experienced AI Voice Developer to build AI receptionists for service-based businesses. This will be an ongoing relationship, not just a one-time project. If you do great work, we expect to send multiple clients every month. Responsibilities Build an AI receptionist that can: Answer inbound phone calls 24/7 Hold natural conversations using an LLM Answer business FAQs Book appointments into the client's booking software/CRM Transfer calls to the business owner when appropriate Send SMS confirmations and follow-up messages Respond to incoming customer text messages Integrate with APIs when needed (BookingKoala, GoHighLevel, HubSpot, Calendly, etc.) Test and optimize the AI before delivery Requirements Experience with Vapi, Retell AI, Bland AI, or similar voice AI platforms Experience integrating CRMs and booking systems through APIs Strong understanding of prompt engineering for voice agents Ability to troubleshoot and improve call quality Excellent communication Ability to deliver projects within 3–7 days To Apply Please answer the following: Which voice AI platforms have you built on? How many AI receptionists have you built? Have you integrated booking software or CRMs before? Have you worked with BookingKoala? Please send 2–3 demo phone numbers or videos of AI receptionists you've built. What is your flat-rate price per AI receptionist? What do you charge monthly for ongoing support? We are looking for a long-term white-label partner who can fulfill projects as we bring in new clients.

I want to create Dream Life Visualization Videos using AI. If you search 'billionaire visualization' videos on yt, this is sort of the style i'm going for but not exactly the same. -Obviously, these videos will be created using realistic AI clips (the longer the clip the better; 20 second clips) -all visuals will be from a first-person point of view -I want sound design on the video to bring the scenes to life -I want to implement consistent characters This first job is a test Before hiring anyone I will need to see previous work (realistic AI video creations) If we have good communication, understanding and you create satisfactory visuals I am looking to work consistently together. I will provide reference images along with descriptions of what I want to be happening in the clip for every clip that will be generated by you. Your job is to create a precise prompt that will create the image scene i'm asking for. YOU MUST BE A PROMPT ENGINEER MASTER, not an amateur that writes prompts and hopes it comes out good. My goal is for each full video to be around 5 minutes long & every clip should is 15-20 seconds long to really give the viewer time to soak in the experience of the scene (that is the point of visualization). This means... (20 sec clips = 15 clips generated) -I want to add dissolve/fade transitions between each clip. -I want every clip to be from the 1st person pov. -Realism is priority.

We are Bowlful a new fresh bowl concept coming to the SODO district of Orlando. We we are aiming to open our doors in October/November 2026. Our BlazeAI account is already set up, connected to all our social channels, and has our branding loaded. Now, we need an expert to activate it. The Goal: We need to start a weekly "Coming Soon" campaign (1 post per landing page week) to tease our arrival and build anticipation in the local market. We want to keep our exact address a mystery until our sign is installed in approximately 60 days. Your Mission: You will be the pilot of our BlazeAI platform. Your primary task is to set up, manage, and fine-tune a 5-month campaign that generates a weekly post. You will use the AI to create content that: Teases our arrival in the SODO area. Highlights our "fresh" concept. Drives our audience to our website for a "sneak peek." Directs the AI to adapt the message as we progress (e.g., sharing pictures of construction, the sign installation, and other milestones). We want to start with one post per week, but as we get closer to opening, we plan to increase the frequency. What We're Looking For: We need a BlazeAI power user. Not just someone who can post, but someone who understands how to train the AI to produce exactly the right tone and content strategy. Key Responsibilities: Campaign Setup: Configure the initial "Coming Soon" campaign within BlazeAI, setting the right goals, topics, and output formats for our brand. Content Direction: Provide ongoing, creative direction to the AI so each weekly post feels fresh, mysterious, and engaging. Quality Control: Review and approve all content generated by the AI before it goes live. Weekly Review: Hop on a 30-minute Sunday call with me to review the upcoming week's posts and discuss any necessary adjustments to the campaign strategy. Performance Analysis: Monitor basic analytics to see what's working and adjust the AI's direction accordingly. Expert-level proficiency with BlazeAI. Strong understanding of AI content generation and prompt engineering within the Blaze ecosystem. Experience managing social media campaigns, especially for local businesses or restaurants. Excellent communication skills for our weekly strategy calls. This is 1-2 hours total a week as the content will generate based on your input and depending how well you lead the AI it will become more and more efficient and require less tweaks. I will review the content on Saturday send over anything I see that I would like adjusted etc. Then our call on Sunday should be very short just to ensure we are on the same page. Long term could be a long term weekly campaign management and grow with our hot start up. As we get closer to the opening we will have many other strategies to employ and the role will expand for the right person as well as the compensation.

About the role We've built an internal tool that automatically generates creative product imagery for e-commerce listings (Amazon, Walmart, Target) — style guides, creative briefs, and finished creative images produced by an AI pipeline. Our client success managers run it day-to-day. What we're looking for is an expert eye above them: someone to audit the output, hold a quality bar, and advise on the technical fixes when the AI gets it wrong. This is an auditor + advisor role, not a production seat. You review and direct; our team executes. What you'll do - Audit AI-generated creative in batches and grade it against a professional standard: composition, hierarchy, typography, color, brand consistency, product fidelity (does the render still look like the real product?), and commercial polish. - Help define and maintain what "ship-ready" looks like, and flag what falls short — and why — in clear, actionable written feedback. - Consult on the technical fixes. When an image comes out wrong (warped product, off-brand palette, bad text rendering, weird "before/after" artifacts), diagnose why at the model/prompt level and prescribe the fix: prompt adjustments, reference-image strategy, model choice, parameters, or editing/inpainting approach. - Partner with our team to translate design problems into technical direction they can implement. You're a strong fit if you have - A professional graphic design background with a portfolio (e-commerce, product, or advertising work strongly preferred) — enough authority to be the one grading the work. - Hands-on experience with modern AI image tools (e.g. Midjourney, DALL-E / GPT image, Stable Diffusion, Flux, Nano Banana / Gemini image, ComfyUI, inpainting/editing, ControlNet or reference-conditioning). - The ability to articulate why an AI image fails and how to steer it — prompt engineering, reference images, seeds, model selection, post-editing. - Strong written communication; your deliverable is critique and direction, so it has to be precise. - Bonus: familiarity with Amazon listing imagery standards, Photoshop/Figma, or light scripting. Not a fit if you only do hand-crafted design and treat AI tools as a black box, or you can generate AI images but can't critique them like a professional designer. We need both — the eye and the technical fluency. Engagement Ongoing, part-time / as-needed advisory. Remote and async-friendly. We'll start with a small paid trial: we share a set of generated outputs, you audit them, deliver written critique against a quality bar, and prescribe technical fixes for the weakest ones. How to apply Send a short Loom video (3-5 min) in which you: 1. Introduce yourself and your design background (share portfolio links). 2. Critique one AI-generated image — walk us through how you assess its quality. 3. Show one AI image that came out wrong and explain how you'd diagnose and fix it at the model/prompt level. 4. Tell us which AI image models/tools you know best and why. Applications that include a Loom video will be prioritized.

Want someone to go over our Retell prompts / get best practices, must be a retell partnered agency. Please share previous projects and the name of your business on retells site.

I’m looking for an AI Engineer to help build an automated red-teaming product based on open-source models. This is a short-term, hands-on project for around 2 months, with an expected commitment of about 20 hours per week. The goal is to build a specialized red-teaming engine that can generate adversarial prompts across different risk domains, severity levels, and attack strategies — then automatically run those prompts against target AI models to identify bad cases, failure patterns, and safety gaps. 🔍 What you’ll work on Build red-teaming systems on top of open-source LLMs, including fine-tuning, prompt optimization, evaluation pipelines, and model orchestration. Design automated prompt generation workflows across risk domains such as self-harm, hate, violence, sexual safety, misinformation, fraud, cyber, and other high-risk areas. Generate prompts across different harm levels, from benign edge cases to policy-borderline and clearly unsafe scenarios, while maintaining structured taxonomies and evaluation criteria. Run automated tests against target models such as Gemma, Llama, Qwen, or other open-source / closed-source models to surface jailbreak patterns, over-refusal, under-refusal, and policy inconsistencies. Build feedback loops that turn model failures into stronger red-team prompts, improved eval sets, remediation recommendations, and continuous safety testing. 🧠 What I’m looking for Hands-on experience with open-source LLMs, fine-tuning, LoRA / QLoRA, RAG, model evaluation, and LLM inference pipelines. Familiarity with AI safety, red teaming, adversarial prompting, jailbreaks, safety evals, or trust & safety systems. Ability to build end-to-end systems, including data pipelines, model serving, eval harnesses, scoring, dashboards, and automation workflows. Bonus if you’ve worked on model safety, content moderation, policy evaluation, agentic testing, or automated eval infrastructure. ⏳ Project setup Duration: around 2 months Time commitment: about 20 hours per week Format: flexible / remote-friendly Stage: early-stage build, from 0 to 1 🚀 Why this is interesting This is not about manually writing red-team prompts one by one. The goal is to build a scalable system that can continuously generate, test, categorize, and learn from model failures — helping teams understand where AI models break, why they break, and how to improve them. If you enjoy working with open-source models, AI safety, red teaming, and fast 0-to-1 product building, I’d love to chat. Feel free to DM me if this sounds like you, or if you know someone who might be a good fit.

**SEO & AEO Strategist** **The role** As Lead SEO & AEO Strategist, you bring a strong SEO background with a deep understanding of AEO and you're the person who raises the analytical bar for the whole team. You are the analytical expert of the team and the voice everyone lean on to make sense of how they show up in AI prompts. You deeply understand our data, reading what's moving and why, and create an actionable plan of recommendations we can act on. You also set the standard for how the rest of the team reads the data and advises clients: mentoring analysts, building the playbooks others run on, and turning your judgment into something we can scale. This is a hands-on, data-first, client-facing role with a clear enablement mandate: you supply the analytical judgment, you deliver it as strategy, and you teach others to do the same. What you'll do Get our brand and clients up and running. Onboarding and get us and clients to value fast, so their accounts are working hard for them from week one. Read the data, find the signal. Analyze how client brands surface across AI answer engines. Identify citation gaps, ranking shifts, and the content patterns that move Share-of-Prompt and our other visibility metrics. Lead working sessions where you take a client's growth and brand goals and map them to a concrete AEO plan, then push on the parts that will move the needle most. Deliver insights and recommendations. Produce the briefs, performance reviews, and optimization plans clients rely on. Translate complex visibility data into clear narratives for both technical and executive audiences. Set the standard and level up the team. Mentor and train others on how to read the data, run a client session, and turn a messy dataset into a recommendation that lands. Define the analytical methods and quality bar others work to, and bring newer team members up to speed on AEO fast. Build the playbooks. Turn your judgment into reusable assets, including analytical frameworks, content playbooks, session templates, and ways of measuring what's working, so the pod's best thinking scales beyond any one person. Support Fix Pack work. Help diagnose what needs fixing and validate that deployed Fix Packs are moving the metrics they should. Flag the exceptions and opportunities that need the team's attention. Work shoulder to shoulder with the pod. Give the Partners and the wider pod the analytical inputs they need: the right numbers, the right context, the right recommended next move. Track the category. Stay current on AEO / SEO developments and how AI answer engines are evolving, so our recommendations stay ahead of a landscape that is constantly shifting. What you need to know (SEO / AEO) This is the foundation of the role. You should already think in terms of how brands earn visibility in AI answers, not just traditional search rankings, and be able to explain that thinking to others. SEO foundations. Solid, hands-on fundamentals: keyword and content strategy, structured data, site architecture, and organic performance analysis, with growing expertise in AI search. Metrics literacy. Comfort reasoning about visibility and performance metrics: reading a shift and understanding what it implies. Category awareness. Familiarity with the AI-visibility tooling landscape, or genuine eagerness to get up to speed fast. What you bring Advisory instinct. You're at ease guiding clients, walking them through a recommendation, and making a technical idea land for a marketing or brand team in plain language. A teaching mindset. You like making other people better at their craft. You can break down how you reached a conclusion, give useful feedback, and turn your own instincts into repeatable methods. Data fluency. Comfortable working with data to find signals. You don't just report numbers, you interpret them. Prompt literacy. Familiarity with prompt engineering and LLM behavior, enough to work effectively inside agent workflows and reason about their outputs. Storytelling. Strong written and verbal communication. You can turn a messy dataset into a clear recommendation for a stakeholder who has thirty seconds. Organized under load. Proven ability to juggle multiple accounts and deadlines without dropping quality. Detail obsessed. Every lift, every point of impact piques your curiosity. Resourceful and proactive. A self-starter who finds creative solutions, adapts quickly, and is comfortable navigating ambiguity and learning new tools. Who you likely are * 4+ years of hands-on SEO or organic-growth work behind you. Agency pedigree is a plus or a comparable data-heavy, client-facing role at a SaaS or AI company. * Someone with an SEO or digital-marketing background who is leaning hard into AI search, or a sharp analyst who's genuinely excited about the AEO category. * Confident on a client call, in a working session, or in a written recommendation, and used to high-touch accounts. * Someone others naturally come to for answers. You've informally or formally mentored, trained, or set the bar for teammates before. * A craftsperson who takes pride in the details while keeping the big picture in mind. * Looking for a role with a clear growth path toward deeper technical and team leadership. 
 Bonus points * You've built reusable things for clients or teams before: playbooks, content frameworks, onboarding material, or ways to measure what's working. * You've worked with enterprise or other high-touch accounts. * You've operated inside a fast-moving, startup.

Job Description: Note: this is about Claude (Anthropic), used by multiple people on our team — not Microsoft Teams integration. This is coaching, not a build-it-for-us project — you'll teach our exec how to do this himself, not deliver a finished system. We're looking for a Claude (Anthropic) super-user to coach a busy executive 1:1 on setting up Claude for team-wide use — shared Projects, Google Drive sync, and ongoing customization — so our team gets consistent, reliable output without him having to rebuild things every time source documents change. This is live, hands-on coaching — not a course, and not a hand-off deliverable. You'll walk him through his actual setup in real time (screen share), show him how to fix and structure it, and leave him able to run it himself. What you'll do: Walk the executive through, live, how to structure shared Claude Projects so multiple team members get consistent, non-conflicting output Show him how to connect and sync Google Drive content into Claude Projects so materials stay current without manual re-uploading Teach him a repeatable process so future document updates reliably reflect in Claude Coach him on customization (Skills, project instructions, memory) for consistent output across the team Leave him with clear, documented steps he can run himself or hand off to someone else What we need from you: Hands-on experience setting up Claude (Anthropic) Projects in a business/team context, including Google Drive sync Strong ability to teach a non-technical executive live — walking him through it, not just doing it for him Comfortable coaching over video/screen-share Bonus: experience rolling out Claude across a team or organization, not just for individual use In your proposal, include an example of a team-based Claude setup you've built — what it did and how you kept it current. Engagement details: 4 hours/week, live sessions, for 2 weeks (8 hours total) — flag in your proposal if you think this scope needs adjusting Video call with screen share, flexible scheduling $80–125/hr depending on experience Possible extension if it's a good fit

Colony Mobility LLC is a Florida-based technology company preparing a Phase I Small Business Innovation Research (SBIR) proposal for the U.S. Department of Transportation under Topic 26-FT1: Person-Centered, Carefree, Complete Trip Planning — Powered by AI. We are seeking a Senior AI Systems and Algorithm Researcher to serve as a named research subcontractor on this federal proposal. This is a research design and documentation role — no production software build is required. What you will research and document: Rider preference engine algorithm — design a machine learning system that learns individual traveler needs over time, including stated preferences, observed behavioral patterns, and inferred preferences for new users Success probability mathematical model — design and write a proof of correctness for a weighted scoring algorithm that calculates the probability a specific rider will successfully complete a specific trip given real-time conditions AI orchestration architecture — document the multi-agent coordination system that assembles, monitors, and replans multimodal trips in real time Outcome learning algorithm — design the reinforcement learning loop that improves system recommendations based on real trip outcomes Trip assembly algorithm pseudocode — document the step-by-step logic for building complete door-to-door journeys from multiple transportation sources LLM integration architecture — document how large language models are used within the system for normalization, preference reasoning, and conversational interfaces What the federal report specifically requires from this role: Algorithm pseudocode for all AI components Mathematical notation and proof of correctness for the success probability model Summary of how ML methods have been used to solve trip-planning problems similar to this solicitation — literature review contribution Justification of how prior research is extended and improved by this system What we need from you before July 3, 2026: A short professional bio (3–5 sentences) describing your relevant background A brief letter of commitment confirming your availability and intent to perform the described work if the contract is awarded Required qualifications: Graduate degree (Master's or PhD) in Computer Science, Applied Mathematics, Data Science, or Artificial Intelligence — or equivalent research experience Demonstrated experience designing machine learning algorithms — preference learning, recommendation systems, optimization, or routing Ability to write mathematical notation fluently — probability models, weighted scoring functions, proofs of correctness Experience writing technical research documentation — academic papers, federal research reports, or technical deliverables for a non-technical audience Familiarity with large language models and their practical limitations in production research contexts Strong plus (not required): Background in multimodal routing algorithms, operations research, or transportation optimization Experience with reinforcement learning or multi-agent systems Prior SBIR, federal research, or government contract experience Published research on routing algorithms, preference learning, or mobility AI Contract details: Hours: 180 hours over 6 months Rate: $120/hour Location: fully remote Start date: September 2026, upon DOT SBIR Phase I award notification Total contract value: $21,600 plus 20% overhead = $25,920

Real Estate Acquisitions Coach — Test & Refine AI Voice Agents We have AI voice agents (inbound, outbound, and speed-to-lead for web leads) that handle motivated seller calls for a real estate investment company. They work — but we need them to sound like a real acquisitions rep, not a bot. **You'll:** - Call into and receive calls from our agents as different seller personas - Try to break them, then tell us what's off - Rewrite robotic lines with language a real rep would use - Flag missing discovery questions and weak objection handling **You are:** - A real estate acquisitions rep / ISA / wholesaler with thousands of seller calls under your belt - Experienced across inbound, outbound, and web lead follow-up - Able to explain *why* a line lands or doesn't **Start:** Paid test / 5 mock calls with Video feedback. Ongoing work if it's a fit. **To apply, send:** 1. How many seller calls have you personally handled? 2. Your best opening line for a 60-day-old lead 3. Your hourly rate Not looking for prompt engineers or copywriters — looking for an operator who's lived in these calls.