Supernormal
Supernormal is your AI-powered meeting platform. Automate meeting notes, agendas, and insights, while Voice Agents help you scale tasks effortlessly—empowering teams to focus on what matters most: building genuine connections and driving.
We're on a mission to transform spoken communication for individuals, teams, and organizations. Meetings are an information-rich channel for productivity, but much is lost due to lack of structure and information flow. At Supernormal we're solving this problem with focus, design, and craft.
Supernormal is a remote-first company and does not require co-location. We have annual team retreats and gatherings several times a quarter.
About the role
Machine learning engineers at Supernormal build the AI that superpowers the core product experience for people's meetings including transcription, note generation, and task automation. The AI team builds reliable and secure services that use the most advanced AI models in the market to generate millions of high-quality meeting notes to a rapidly growing customer base. Our work revolves heavily around software engineering, too – we are looking for people with a drive to roll up their sleeves and get new models and features out to users as quickly as possible.
What you'll work on
As an ML Engineer on Supernormal's AI team, you'll lead the full development cycle of AI solutions for meeting notes, question answering, agent conversations, and task completion. Your responsibilities will include:
- Prompt engineering using state-of-the-art techniques to improve the 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.
- Improving our LLM-powered search and question answering using retrieval augmented generation (RAG), everything from defining and improving quality metrics to optimizing our infrastructure.
- Advocating for, and building, new and better ways of doing things.
RequirementsWhat you will bring
- 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.
- 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.
- Proficient in Python: our AI stack uses Python and interfaces with Ruby on Rails and Typescript.
What we'll expect of you
- A collaborative mindset, focused on lifting others and improving daily.
- A drive to tackle tough problems and do hard things.
- High agency and initiative in bringing and building ideas.
- Willingness to learn and improve existing approaches.
- Emphasis on shared ideas and collective responsibility.
- A growth mindset when facing challenges, aiming for team improvement.
What you can expect from us
- We're a fully distributed team spread between Pacific Time (California) and Central European Time (Stockholm).
- We're a friendly bunch and are happy to pair, talk through, or otherwise assist any time.
- Honest and timely feedback.
- A willingness to listen to your ideas.
- A respect for your time outside of work.
Full healthcare coverage (Medical, Dental, and Vision)
Totally remote. Not hybrid. Remote. No return-to-office here.
WFH budget to make sure you have everything you need to do your best work.
Education credit (up to $500 per year).
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