UX Designer - AI & Data-Driven Nature Tools at WildMon | Torre
UX Designer - AI & Data-Driven Nature Tools
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WildMon

UX Designer - AI & Data-Driven Nature Tools

WildMon
Posted by
Shayan Azhar
Emma
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Freelance
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GMT-06:00 to GMT-00:00
Posted 2 months ago

Responsibilities and deliverables

We’re looking for an experienced UX Designer to help shape Chorus, an AI-powered platform for acoustic biodiversity monitoring funded by the Bezos Earth Fund in partnership with the National Audubon Society. Joining a product in active development, you'll work closely with the Product Lead and development team to rapidly turn ambiguous product and technical challenges into intuitive, implementable UX solutions. This role requires an experienced designer who can quickly onboard, take ownership, move quickly from ideas to wireframes, and make sound UX decisions with minimal direction. What You’ll Do - Translate complex requirements into simple, intuitive user experiences. - Rapidly explore, validate, and iterate UX solutions through wireframes and user flows - Work with the Product Lead to explore solutions and validate assumptions through lightweight research and usability testing. - Collaborate with developers to ensure designs are practical, light, consistent, and ready for implementation. What We’re Looking For - UX Designer with 4+ years of experience designing complex workflows and a strong product mindset. - Exceptional ability to simplify complex concepts into intuitive interfaces. - High degree of autonomy in exploring UX solutions, making design decisions, and driving work forward. - Organized and reliable, with the ability to define priorities, manage timelines, and consistently meet deadlines. - Fast and iterative, sharing work early and responding effectively to feedback. - Strong proficiency with Figma and FigJam, including wireframing, UX flows. - Experience with AI, data-driven, or similarly technical products. Upcoming Challenges As Chorus continues to evolve, you'll help design major upcoming capabilities expanding the complexity of AI-powered species search and validation, accessible workflows for training custom machine learning models, and integration with biodiversity dashboards.
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