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MindWave (YC W22) is hiring Full-Stack Engineer(mindwave.ai)

1 point by mindwave_inc 2 years ago flag hide 14 comments

john99 2 years ago next
[original post] MindWave (YC W22) is hiring Full-Stack Engineer. Join our team and work on cutting-edge AI technologies. Apply at https://mindwave-jobs.com/full-stack-engineer.
- codezilla 2 years ago next
  Just applied! Excited to see what you're working on. MindWave has always been at the forefront of innovation.
  john99 2 years ago next
  @codezilla Thanks! Our main focus right now is improving conversational AI with our new MindNet neural network architecture.
  aiwiz 2 years ago prev next
  @codezilla They also have some exciting projects related to deep learning and NLP that they will be revealing soon. Keep an eye on their updates!
- technoholic 2 years ago prev next
  Same here, can't wait to see the problems you're trying to solve. Good luck with the recruitment process!
qwerty45 2 years ago prev next
How do you manage ML model training at scale? Do you rely on on-premise resources or leverage cloud solutions like GCP or AWS?
- john99 2 years ago next
  @qwerty45 We primarily use Google Cloud to train our models. For large-scale tasks, we utilize GPUs on the cloud-based virtual machines for speed. We recently switched from AWS to GCP due to its better support for ML workloads.
- machineking 2 years ago prev next
  @qwerty45 Considering the amount of data MindWave might process, I'd suggest taking advantage of managed ML services from a cloud provider. A scalable and efficient solution can be implemented with little effort in the long run.
mikey 2 years ago prev next
What kind of engineering challenges can a Full-Stack Engineer expect working on this project? Would be great to hear about some real-world problems that need solving!
- john99 2 years ago next
  @mikey Some challenges include customizing UI components that accommodate AI (ML) model outputs, creating scalable backend infrastructure for real-time communication between clients and models, and handling enormous datasets for model training. For example,
  john99 2 years ago next
  we have a few challenges right now with our conversational AI system where it sometimes struggles to distinguish context for corrections and maintaining the conversation smoothly. Currently, we're focusing on a feature where the AI can clarify ambiguous statements and improve its understanding of user intentions.
- kevin01 2 years ago prev next
  @mikey I can also speak from experience when I say you'll work on a myriad of frontend and backend libraries and tools, from Angular, React, Vue.js to Flask, Node.js, and more. It certainly keeps things interesting around here!
hrinstructor 2 years ago prev next
What is the interviewing process like, and what background are you looking for in candidates?
- john99 2 years ago next
  @hrinstructor Our interview process typically entails behavioral questions, coding challenges, and a system design round. As for background, experience in AI, ML, and NLP, including some exposure to server-side development is highly desired.

john99 2 years ago next
[original post] MindWave (YC W22) is hiring Full-Stack Engineer. Join our team and work on cutting-edge AI technologies. Apply at https://mindwave-jobs.com/full-stack-engineer.
- codezilla 2 years ago next
  Just applied! Excited to see what you're working on. MindWave has always been at the forefront of innovation.
  john99 2 years ago next
  @codezilla Thanks! Our main focus right now is improving conversational AI with our new MindNet neural network architecture.
  aiwiz 2 years ago prev next
  @codezilla They also have some exciting projects related to deep learning and NLP that they will be revealing soon. Keep an eye on their updates!
- technoholic 2 years ago prev next
  Same here, can't wait to see the problems you're trying to solve. Good luck with the recruitment process!
qwerty45 2 years ago prev next
How do you manage ML model training at scale? Do you rely on on-premise resources or leverage cloud solutions like GCP or AWS?
- john99 2 years ago next
  @qwerty45 We primarily use Google Cloud to train our models. For large-scale tasks, we utilize GPUs on the cloud-based virtual machines for speed. We recently switched from AWS to GCP due to its better support for ML workloads.
- machineking 2 years ago prev next
  @qwerty45 Considering the amount of data MindWave might process, I'd suggest taking advantage of managed ML services from a cloud provider. A scalable and efficient solution can be implemented with little effort in the long run.
mikey 2 years ago prev next
What kind of engineering challenges can a Full-Stack Engineer expect working on this project? Would be great to hear about some real-world problems that need solving!
- john99 2 years ago next
  @mikey Some challenges include customizing UI components that accommodate AI (ML) model outputs, creating scalable backend infrastructure for real-time communication between clients and models, and handling enormous datasets for model training. For example,
  john99 2 years ago next
  we have a few challenges right now with our conversational AI system where it sometimes struggles to distinguish context for corrections and maintaining the conversation smoothly. Currently, we're focusing on a feature where the AI can clarify ambiguous statements and improve its understanding of user intentions.
- kevin01 2 years ago prev next
  @mikey I can also speak from experience when I say you'll work on a myriad of frontend and backend libraries and tools, from Angular, React, Vue.js to Flask, Node.js, and more. It certainly keeps things interesting around here!
hrinstructor 2 years ago prev next
What is the interviewing process like, and what background are you looking for in candidates?
- john99 2 years ago next
  @hrinstructor Our interview process typically entails behavioral questions, coding challenges, and a system design round. As for background, experience in AI, ML, and NLP, including some exposure to server-side development is highly desired.