What are the responsibilities and job description for the Senior Product Engineer position at Aitopics?
Nooks
The Nooks AI Sales Assistant Platform automates busywork in dialing, coaching, and prospecting to 3x pipeline generation.
Nooks is a platform transforming sales reps from manual laborers to scientists. With today’s technology, sales reps shouldn’t need to manually write hundreds of emails, research hundreds of websites / LinkedIn, and make hundreds of calls. They should instead focus on the parts of their job that actually require people - talking to customers, being creative, and problem-solving. With a combination of AI tools, automation, and real-time collaboration, Nooks can do the rest.
The Role
We have an ambitious product vision in a nascent area - AI-powered real-time collaboration - so there are a ton of interesting technical challenges on our roadmap. We’re hiring talented full-stack / backend / ML engineers who are product-minded and excited to delight our customers. We expect every software engineer on our team to be able to work within a complex code-base, own entire product areas, and build new features end-to-end.
Examples of Engineering Problems We’re Working On
These are just examples, this list is non-exhaustive, and you definitely don’t need experience in all of these areas. But hopefully you find some of them exciting!
- Concurrency & distributed systems - Our smart dialer places calls in parallel and runs a real-time AI model on each call. There are some interesting concurrency problems syncing state between Twilio, our backend, and the frontend, and knowing which calls to connect, which to continue in the background, and when to start the next call.
- Real-time audio AI & precision / recall / latency tradeoffs (algorithms & models) - We use audio data, transcription, silence detection, and several other signals to detect whether a live phone call is a voicemail, a human, or a dial tree. Here, latency is a third factor added to the standard precision / recall tradeoff because it’s important we can detect humans quickly.
- Latency (infrastructure) - If our model took 5 seconds to detect a human on a phone call, the human would hang up. It’s imperative we can detect quickly and that our users can execute calls quickly.
- Smart call funnels & playbooks (data wrangling, backend eng, GPT-3, UX) - We’re using GPT-3 and other LLM’s to turn companies’ mostly unstructured call data into actionable strategies & feedback loops.
- Conversation embeddings & markov models (ML modeling) - Can we use LLM’s to generate embeddings of conversations that we can use to cluster similar conversation patterns and predict where the conversation is headed?
- Integrations - Our dialer integrates with customers’ sales engagement platforms. When building integrations, we need to make sure they’re robust, reliable, and well-abstracted.
- Frontend performance - There’s a lot going on in the frontend - WebRTC, Twilio, React rendering, websockets, etc. And people use Nooks throughout the workday, so we need to make sure our app is performant across a wide range of devices.
Requirements
We offer competitive compensation because we want to hire the best people and reward them for their contributions to our mission. The target salary range for this role is $140,000 - $240,000. On top of base salary, we also offer equity, generous perks, and comprehensive benefits.
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Salary : $140,000 - $240,000
