We are rethinking how people and companies interact with contracts. We are serial entrepreneurs backed by Berkeley SkyDeck, Plug & Play VC, Rockstart and LexLab at UC Hastings.
We are a Machine Learning startup based in California and we are looking for a motivated Machine Learning Researcher for a legal AI product.
About us
Have you ever signed a contract but not really understood what it said? Us too.
Contracts are the foundation of all commerce, but they're basically impossible to understand. They're dense and filled with jargon. Oftentimes, they're literally written in Latin.
SpeedLegal SaaS platform helps busy professionals e.g. salespeople and buyers close deals 3X faster (200% revenue accelerator) and save ~$60k-140k in legal fees when reviewing contracts.
About you
You are able to program in Python, and you are familiar with modern Deep Learning and NLP theory and main techniques, such as Transformers, Named Entity Recognition, word embeddings and text classification.
Ideally, you would have applied these techniques in a commercial setting already, but we are very keen also to hear from students or Deep Learning enthusiasts who can show ability to work in the area.
Your task will involve creating an MVP that shows feasibility. We already won the Stanford hackathon and we validated the customer segment and the problem.
What’s in it for you
You will get to practice and improve your Deep Learning and NLP techniques, within an exciting startup. We will provide cloud computing capabilities, to enable you to work on the models.
Initial duration for the internship is 3 months, which can be extended.
Location: Remote
If this role sounds like a good fit, we’d love to hear from you! Think you are missing some of the skills and are hesitant to apply? We do not believe in the ‘perfect’ candidate and encourage you to apply if you feel you can bring value to our team!
Please send your resume when applying.
SpeedLegal is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, colour, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.