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Job Overview
Location
Indiana, USA
Job Type
Full-time
Category
Marketing
Date Posted
October 3, 2025
Full Job Description
đź“‹ Description
- • Own the entire growth and distribution engine for Pluralis Research, translating world-class AI breakthroughs into stories that resonate far beyond the lab. You’ll be the bridge between frontier research and the wider world—crafting narratives, securing headlines, and building communities that amplify our mission.
- • Build and nurture the Pluralis community from the ground up: run our Discord, own our X presence, and design events that turn researchers, builders, and curious outsiders into evangelists. You’ll set the tone, moderate debates, surface insights, and make every member feel like an insider.
- • Drive relentless, high-signal distribution of Protocol Learning across press, podcasts, newsletters, and technical media. You’ll pitch journalists, book podcast tours, ghost-write op-eds, and land features in venues that matter—from arXiv buzz to mainstream tech outlets.
- • Distill dense ML research into crystal-clear narratives for general audiences without dumbing anything down. You’ll translate training-loss curves, attention-layer tweaks, and PyTorch wizardry into threads, explainers, and keynote talks that both PhDs and product managers can love.
- • Draft and schedule daily content for all official Pluralis channels. You’ll balance speed with substance, hype with humility, and ensure every post, slide deck, or event recap reinforces our brand as the most credible voice in decentralized AI.
- • Plan and execute flagship events and guerrilla side-events around NeurIPS, ICML, and other key conferences. You’ll coordinate scientist speakers, wrangle sponsors, design swag, and turn 30-minute poster sessions into week-long conversation domination.
- • Build and leverage a powerful network of journalists, podcasters, newsletter authors, and community influencers. You’ll maintain a living CRM of contacts, negotiate exclusives, and keep Pluralis top-of-mind when news breaks or trends emerge.
- • Contribute directly to marketing strategy as an individual contributor—no bloated team, no red tape. You’ll test channels, measure impact, double-down on what works, and sunset what doesn’t, all while reporting directly to the founder.
- • Operate with extreme autonomy and bias for action. You’ll ship first, iterate fast, and treat every experiment—whether a meme, a Medium post, or a pop-up dinner—as data that sharpens the next move.
- • Champion non-standard backgrounds and unconventional paths. Whether you dropped out of a PhD program, ran a cult Substack, or scaled a DeFi community, your lived experience is the credential we value most.
🎯 Requirements
- • Demonstrated track record of securing press, podcast, or keynote placements that moved the needle for a technical brand or product
- • Exceptional writing ability—can translate complex ML topics into accessible, hype-free content that retains scientific rigor
- • Prior success building and growing a technical audience (Discord, newsletter, Twitter, or equivalent) from <1k to 10k+ engaged members
- • Working familiarity with core ML concepts—training loss, PyTorch internals, attention mechanisms—gained through coursework, side projects, or industry exposure
- • Experience supporting founder-led marketing in a fast-moving, pre-Series B startup environment
🏖️ Benefits
- • Direct line to the founder and a true seat at the strategy table—zero layers of bureaucracy
- • Budget and autonomy to experiment with any channel, event format, or creative idea you believe will cut through the noise
- • All-access pass to the world’s top AI conferences, plus travel budget to host and attend satellite events
- • Competitive cash compensation plus meaningful equity in a company redefining decentralized AI research
Skills & Technologies
PyTorch
Senior
Onsite
About Pluralis Research Ltd
Pluralis Research develops a novel approach to training large AI models called “Protocol Learning.” Instead of traditional centralized or open-source models, their method enables decentralized, multi-participant model training where no single party ever holds a full copy of the model weights. This makes models “unextractable” and supports collaborative ownership, allowing value from model usage to flow back to contributors. They aim to democratize access and innovation in AI, reduce dependency on large tech firms, and create a sustainable, open ecosystem for foundation model development.
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