Company Overview
Scribe is a fast-growing productivity startup with over 500,000 users who document and share how work gets done in seconds. Scribe has been used to document millions of workflows and contains a treasure trove of interesting data on how work gets done - giving us a unique starting point for applying machine learning to product development.
Job Overview
We are hiring our first ever Machine Learning Product Engineer at Scribe. The ideal candidate loves experimenting with new ML tech and is excited by the opportunity to apply it alongside a team of like-minded, fast-moving builders. If you're passionate about real-world applications of ML with immediate user impact — and have experience building Python ML projects for work, academics, or fun — we’d love to hear from you!
Responsibilities:
- Work with the CTO, as well as the product management and engineering teams, to identify opportunities for using machine learning to improve the Scribe user experience.
- Experiment with different approaches to using large language models to enable new functionality in our product.
- Design, develop, and test machine learning models that can be integrated into our product.
- Stay up-to-date with the latest research and developments in machine learning and natural language processing, and apply these insights to improve our product.
Requirements:
- Excellent blend of creativity, problem-solving, and analytical skills
- Experience with deep learning frameworks such as TensorFlow or PyTorch and/or LLM tools like LangChain, LlamaIndex, and the OpenAI APIs
- Python programming skills
- Strong communication and collaboration skills
Preferred:
- A degree in Machine Learning, Computer Science, Electrical Engineering, or a related field.
If you are a self-motivated individual with a passion for using machine learning to build innovative products, we would love to hear from you.
Compensation
$120k-180k USD salary (yearly gross) + equity
Unsure if you meet all of these requirements? Please apply anyway! We would love to hear from you.