Advanced Conversational AI Engineer
1 week ago
Supernormal is revolutionizing spoken communication for individuals, teams, and organizations. We're on a mission to make meetings more productive by solving the problem of information flow and structure.
We've been working on this since 2019, serving customers like Snap, Salesforce, Replay, Gitcoin, Pinterest, and thousands more. We're growing rapidly and are excited to have new team members join us.
We're a remote-first company that doesn't require co-location. We have annual team retreats and gatherings several times a quarter.
About the RoleThis Advanced Conversational AI Engineer position involves building AI that superpowers our core product experience for people's meetings, including transcription, note generation, and task automation. The AI team creates reliable and secure services using the most advanced AI models in the market to generate high-quality meeting notes for a rapidly growing customer base.
The work revolves heavily around software engineering, requiring candidates with a drive to roll up their sleeves and get new models and features out to users quickly.
Key Responsibilities- Lead the full development cycle of AI solutions for meeting notes, question answering, agent conversations, and task completion.
- Prompt engineering using state-of-the-art techniques to improve core meeting assistant scenarios.
- Building and shipping machine learning models to improve transcript quality, reduce API token usage, eliminate LLM output defects, and extract semi-structured data.
- Training and deploying custom language models (LoRA, RLHF, instruction-tuning, etc.), fine-tuning models for diverse business needs.
- Creating new NLP & LLM-driven product experiences that improve with user feedback, collaborating with product and design teams.
- Production-level AI/ML Experience: Demonstrated proficiency in AI/ML with a track record of at least 3-5 years' experience building machine learning systems.
- Experience delivering products and services using GenAI: 1+ year experience building NLP systems using LLMs, including proficiency with data curation/cleaning/labeling, fine-tuning/training models, and evaluating generative text output.
- Software Engineering Competency: A solid engineering background with a robust foundation in software engineering principles.
- A Solid Educational Foundation in AI/ML: Bachelor's degree in Computer Science, Engineering, AI, Mathematics, or related field; Master's degree or PhD a plus.
- A competitive salary ($175,000 - $250,000 per year)
- 401K plan
- Stock options
- Full healthcare coverage
- Totally remote work environment
- WFH budget to ensure you have everything needed to do your best work
- Annual team-wide offsite to a cool location
- Education credit (up to $500 per year)
- Unlimited PTO (minimum 4 weeks)
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