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Job Location: New York, NY
Job Detail:
About The Role
Join a small and mighty team of engineers at Supernormal working on pulling the future of work closer to the present. Each engineer here is responsible for saving people thousands of hours of manual work every month, and we’re just getting warmed up.
As a machine learning engineer, you’ll focus on building and improving the AI stack powering Supernormal’s productivity suite. You’ll work closely with our product engineers and designers to evolve the AI along with the product.
What you’ll work on
- Prompt engineering using state-of-the-art techniques to improve the core meeting assistant scenarios
- Fine tuning, assessing, and deploying large language models
- Developing and improving business and product metrics driven by the quality and cost of AI usage
- Designing, training and deploying custom machine learning models to augment the AI stack, e.g. to manage transcript quality, compress text without losing semantic meaning, remove defects, incorporate semi-structured data
Requirements
What we’ll expect of you
- You have a strong working background in machine learning, NLP, and large language models
- A collaborative and open outlook — we’re all about lifting each other up and getting better every day. You should be, too.
- A willingness to get deep into a problem even when it seems impossible. You’ll always have support from the team.
- Confidence operating with high agency. We’ll work together to decide what’s important, but we’d love for you to bring (and build!) your own ideas.
- You’ll leave “it works on my machine” at the door. You know better than to trust computers.
- You’ll come in willing to learn why things are the way they are, then suggest a better way.
- You’ll understand that there’s no difference between “my code” and “their code.” It’s our code and we’re all responsible for it.
- You’ll approach code review through a “how can the team level up?” lens — let’s all get better, together.
What you can expect from us
- The team’s full support. We’re a friendly bunch and are happy to pair, talk through, or otherwise assist any time.
- Honest and timely feedback. We’re all better when we can have candid conversations about what is and isn’t working.
- A deep willingness to listen to your ideas: how can the codebase, our product, or team be better?
- A respect for your time outside of work. We all work hard here, but we never forget to rest and have fun.
Benefits
Competitive salary
Stock options
Full healthcare coverage (Medical, Dental, and Vision)
Flexible hybrid working model
WFH budget to make sure you have everything you need to do your best work
✈️ Annual team-wide offsite to someplace cool
Education credit (up to $500 per year)
Unlimited PTO (minimum 4 weeks)
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