Datology AI

Datology AI

Marketing Manager

Redwood City

Sponsorship not specified$130k-$175kDetected 30 days ago
Data EngineeringProject ManagementLogisticsCadenceResearch

About the role

  • As the first Marketing Manager, you'll work closely with our VP of Marketing to be the operational backbone of a content-led, founder-driven marketing motion at a research-credible AI infrastructure company.
  • You won't be running an existing process
  • We have a lot in flight, the playbook is being written, and we need someone agile, flexible, and willing to roll up their sleeves and get stuff done!

Responsibilities

  • You'll take operational ownership of the key programs and events that drive this motion, such as research launches, conferences, executive dinners, and our social media presence. You won't be running an existing process
  • Content calendar and operating rhythm. Build and maintain a rolling content calendar that tracks each piece, its owner, the date, and its status, and keep the team on schedule against publish dates.
  • Publishing operations. Schedule and post on X and LinkedIn for the company accounts and the founders; run the publishing pipeline; maintain posting cadence; and reuse content across channels.
  • Blog and website. Post to the blog, manage the publishing process, and make website updates, including copy changes and media asset updates.
  • Measurement and reporting. Build and maintain the monthly executive dashboard and quarterly reporting. Keep the underlying data up to date and deliver the report on time so the team can see how reach, engagement, and pipeline are tracking.
  • You'll take operational ownership of the key programs and events that drive this motion, such as research launches, conferences, executive dinners, and our social media presence.

Nice to have

  • Familiarity with AI-driven content workflows and modern publishing automation
  • Experience supporting founder-led or executive content programs
  • A track record of running technical product launches end-to-end
  • Don't meet every single requirement?
  • We still encourage you to apply.
  • The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.
  • 401(k) plan with a generous 4% company match.

Compensation

  • At DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The salary for this position ranges from $130,000 to $175,000.
  • The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.
  • 401(k) plan with a generous 4% company match.
  • Annual $2,000 wellness stipend.
  • Annual $1,000 learning and development stipend.
  • Daily lunches and snacks are provided in our office!

Benefits

  • 100% covered health benefits (medical, vision, and dental).
  • Unlimited PTO policy
  • Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
  • Annual $2,000 wellness stipend.
  • Annual $1,000 learning and development stipend.
  • Our benefits are built to support your well-being and growth:

Company info

  • Models are what they eat.
  • But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy.
  • At DatologyAI, we've built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models.
  • For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner's Fallacy https://www.datologyai.com/blog/finetuners-fallacy).
  • We raised a total of $57.5M in two rounds, a Seed and Series A.
  • This role is based in Redwood City, CA.
  • We are in office 4 days a week.
  • Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment.
  • Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models.
  • Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data.
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