AssemblyAI (S17)
#1 Speech-to-Text API for Developers

Growth Marketer

Remote
Full-time
3+ years
About AssemblyAI

AssemblyAI is the #1 rated API for Speech Recognition. Thousands of developers use our APIs to transcribe millions of videos, podcasts, phone calls, and zoom meetings every day - powering innovative products like visual voicemail, meeting summarizers, and closed captioning.

We're backed by leading investors including Y Combinator, John and Patrick Collison of Stripe, Daniel Gross, and Nat Friedman. We were founded in 2017.

About the role

About us

AssemblyAI is the #1 rated API for speech recognition. Thousands of developers use our APIs to transcribe millions of videos, podcasts, phone calls, and zoom meetings every day - powering innovative products like visual voicemail, meeting summarizers, and closed captioning.

We're backed by leading investors including Y Combinator, John and Patrick Collison of Stripe, Daniel Gross, and Nat Friedman. We were founded in 2017.

Responsibilities

We're looking for an experienced Growth Marketer to join our team. Some of the things you'd work on would include:

  • Run, track, and optimize paid search and paid social campaigns
  • Develop and run email marketing campaigns to engage and convert free customers to paid plans
  • Work with our front-end team to build out and optimize landing pages to improve conversion rates
  • Analyze performance metrics (Google Analytics, conversion rates, etc) to optimize marketing strategies and campaigns

As one of the first marketers on the team, you'd have a lot of autonomy and ownership over the entire process - from developing growth marketing strategies to executing them.

Apply

If you're interested in this role, please fill out the application form here: https://forms.gle/zrAdKfP89nHLZDDeA.

Benefits

  • Competitive salary
  • Platinum healthcare
  • Dental care and vision
  • Unlimited PTO
  • Equity
  • Fully remote
  • $1k budget for home office equipment

Technology

All of our Deep Learning models are trained in PyTorch on extremely large in-house datasets, across dozens of v100s, in our dedicated training clusters. For our production stack, we deploy everything into a modern Python micro-service architecture in AWS (Flask, Tornado, Docker, etc).

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