Responsibilities: Responsible for product design, conceptualization and ideation, and technical integration. This will entail creating user interfaces, designing user journeys, developing visual designs, establishing design systems for Replicate’s machine learning tools and platforms; developing new concepts for machine learning workflows, models deployment processes, and team collaboration features; and working with developers to implement user interfaces, ensure technical feasibility of designs, and optimize designs for developer tools and APIs. Travel required for domestic biannual summits. Telecommuting permitted locally but in office presence is encouraged.
Requirements: Bachelor's degree in Human-Computer Interaction, Design, Computer Science, or related field. Degree must include coursework in user interface design, software development principles, and interactive systems and 8 years of experience as Head of Design, Design Lead, Principal Designer, Senior UX Designer, Product Design Lead, User Experience Engineer, Design Systems Engineer, or Developer Experience (DX) Designer. Must also possess: 8 years of experience with: Developer productivity tools and platforms; Enterprise software; Workflow optimization; End-to-end product design; Modern front-end development; Developer workflows, toolchains, and productivity optimization; Conducting user research with technical audiences, synthesizing feedback from developers and engineering teams, and translating findings into actionable product designs; Leading design sprints and facilitating collaborative design workshops, with proven ability to align stakeholders around complex technical requirements; Measuring and optimizing for developer experience (DX); and Managing cross-functional product design projects from conception to launch, particularly in the context of developer tools and enterprise software platforms. Must successfully pass competency-based interview. Expected salary range is $245,700-$335,000/year. To apply, send resume to jobs@replicate.com.
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Machine learning can now do some extraordinary things, but its still hard to use. You spend all day battling with messy Python scripts, broken Colab notebooks, perplexing CUDA errors, misshapen tensors. Its a mess. The reason machine learning is s...
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