Come build what doesn’t exist yet.

We’ve launched our Beta and we’re ready to level it up. We’re looking for a freelance Product UX/UI Designer to help shape the next chapter of Yoree and its related digital touchpoints. You’ll work closely with our Chief Experience Officer on developing the roadmap and bringing fresh thinking to how the product looks, feels and works.

This isn’t a “here’s a ticket, go” role. We want someone who enjoys exploring ideas, challenging the brief and working collaboratively through different directions before landing on the right answer.

• Collaborating with our Chief Experience Officer to help define and evolve the product roadmap.
• Designing new features and flows as we scale the app, from early concept through to polished UI.
• Exploring multiple directions for key product problems, and testing ideas against user needs and the brand experience.
• Rapidly prototyping ideas, user flows and scenarios to evaluate concepts.
• Building on and evolving our Figma design system.
• Extending your thinking beyond the app into other digital touchpoints, including evolving websites.
• Bringing a human-centred lens to everything, grounding ideas in how real people think and behave, not simply what looks good.

• A mid-to-senior UX/UI designer with a strong portfolio of product design work.
• App design experience is required.
• Confident working in Figma.
• Ideally experienced in building or contributing to design systems.
• Able to think critically, ask good questions and turn ambiguity into clear, human-centred concepts.
• Comfortable in a fast-moving, agile environment where priorities can shift.
• Collaborative and confident presenting ideas, taking feedback and iterating openly.
• Self-directed and reliable when working remotely.
• Flexible availability for project-based work.
• Strong English-language communication skills for collaboration with the UK-based team.

• Experience designing for early-stage or scaling products.
• Animation and video experience.
• Strong interaction design capability.
• An excellent eye for motion and micro-interactions.

Send us your portfolio and a short note explaining why this sounds like your kind of project. We’re especially keen to see app-design examples that show how you’ve approached ambiguous problems and worked with a design system.

We’re a small team building a live consumer app for capturing, organising and reliving personal memories: iOS and Android, built with Expo / React Native on a serverless AWS backend. It’s shipping and in active development, and we’re bringing on an experienced mobile engineer to help build out the roadmap.

You’d own features end to end: UI, app logic, backend data and functions, tests, and releases. Real ownership, small team, fast feedback.

• A multi-step memory-creation flow: photo selection, AI-assisted captions, people tagging, story authoring, and an animated memory viewer.
• Resumable background media uploads and image/video processing.
• Auth: email/password, Google and Apple sign-in, biometrics, account recovery.
• Local and background notifications.
• In-app subscriptions.
• Building designs from Figma against a Tailwind-based component system, light and dark.
• Internationalisation across four languages.
• Native build and release pipelines, and over-the-air updates.

• 4+ years building production React Native apps, with strong Expo experience (recent SDKs, dev-client / prebuild).
• Strong TypeScript.
• File-based routing (Expo Router) or React Navigation at scale.
• Hands-on AWS: authentication, a NoSQL datastore, serverless functions, object storage (AWS Amplify Gen 2 is a plus).
• Comfort with native tooling: Xcode, Android Studio, CocoaPods, config plugins, EAS Build.
• Animated, gesture-driven UI with React Native Reanimated.
• A real testing habit: Jest + React Testing Library, and an E2E tool such as Maestro or Detox.
• Self-direction in a Git PR workflow with CI, able to run with light oversight.

Background tasks and offline sync · NativeWind / Gluestack UI · RevenueCat and app-store review · push/local notifications · i18next · Sentry · OTA update strategy · AWS CDK · Figma-to-code

AI coding assistants are welcome and expected. You own what you submit: it passes CI, matches our conventions, and you can explain any line in review. The harder native and backend work still needs genuine understanding. That is the part we’re really hiring for.

Expo · React Native · TypeScript · Expo Router · AWS Amplify Gen 2 (Cognito, DynamoDB, Lambda, S3) · Gluestack UI + NativeWind · Reanimated · RevenueCat · i18next · Jest · Maestro · EAS Build + Submit · OTA updates

Send your day rate, availability, a React Native / Expo portfolio or code samples, and a short note on a background-upload or offline-sync problem you’ve solved on mobile.

We build a consumer mobile app for capturing and reliving personal memories. Two of its features are AI-generated: a short narrative story built from a set of photos and their metadata, and a per-photo caption. Both run server-side on AWS Bedrock today, and we want to know whether we can do better.

This is a time-boxed research and evaluation spike of roughly a week, scoped as a standalone deliverable. It can run ahead of or alongside a longer engagement.

• Can a different model, an open-weight model on Bedrock or a small custom fine-tune, meaningfully improve quality at the same or lower cost per call? Cost is already about 1¢ per story, so the bar is quality, not spend.
• What would it take to move part of this on-device on iOS and Android, especially the multimodal caption step, and what does that cost us in quality, engineering and maintenance?

Frontier hosted models (GPT, Claude Opus/Sonnet) are out of scope as production options; we use one only as a quality-reference ceiling.

• Understand the current pipeline: structured photo metadata in, JSON story/caption out.
• Build a small eval harness and a dataset of real, anonymised examples, plus a human-written “gold” reference set.
• Benchmark a shortlist of candidates, open-weight LLMs for the story and open vision models for the caption, using an LLM-as-judge plus a short human blind rank.
• Produce a $-per-1,000-calls and latency table from measured token counts.
• Assess the on-device options (Apple Foundation Models, Gemini Nano / ML Kit, ExecuTorch / llama.cpp) against the same references.
• Deliver a written go / no-go recommendation per feature, with effort estimates.

• Hands-on experience evaluating and shipping LLM features: not just prompting, but structured evaluation, LLM-as-judge, and cost/latency analysis.
• Familiarity with the current open-weight landscape (Qwen, Llama, Mistral, DeepSeek, GLM, and vision models) and where to find reliable benchmarks.
• AWS Bedrock experience, or equivalent with another hosted-inference platform.
• Comfort reading a Python codebase and writing a clean eval script.
• Bonus: LoRA / small-model fine-tuning; on-device inference on mobile (Core ML, ExecuTorch, MLC, llama.cpp); multimodal models.

• Eval harness and dataset, committed to our repo.
• A results document: scored comparison per feature, cost/latency, sample outputs, multilingual-capability notes, and an on-device feasibility summary.
• A clear recommendation and next-step effort estimate.

Send your rate, availability, and a short example of a model evaluation or comparison you’ve done, ideally something where you had to weigh quality against cost.