Member of Technical Staff - Research
Basis
About Basis
Join at the leading edge of applied ML, as we deploy agents against real enterprise use cases in the accounting world.
Basis is an AI platform for accounting firms, providing accountants with a team of AI assistants. Accounting teams delegate core workflows to Basis, automating time-consuming, manual work.
The team is growing exceptionally quickly (we’ve doubled headcount over the last three months) and we need your help. We’re looking for people who crave ownership and want to move fast.
📍 Location: NYC, Flatiron office. In-person team.
Your role
Build
Train agents to solve accounting
Stay up-to-date on applied research to inform our design decisions
Take ownership
Work closely with ML research, co-founders, and rest of team
Own internal benchmarks and evaluations
Own LLM experimentation
Set culture and practice
Shape our ML culture and processes, including around internal use of LLMs for ML and engineering
Learn
You'll be surrounded by a team pushing the bounds of applying LLMs to real world problems. Expect to have to learn a ton both on technical and domain-specific topics
Wear multiple hats
Balance long-term thinking/ smart abstractions with shipping fast and iteratively
Help hire and build out the growing ML research team
Are you the one?
Research Engineers at Basis should be strong first-principles thinkers, eager to learn by doing.
Essentials
-
ML engineering: Experience building out some production ML systems:
End-to-end from concept to production
Interest in LM post-training, Reinforcement Learning, NLP
Experience: 2-4 years of experience in ML; for candidates with fewer years, looking for evidence of exceptional ability
First principles reasoner: Ability to break complex concepts down to their fundamentals and then build from there
Scrappy: Ability to iterate quickly in near-term while planning for long-term
Flexibility: Willing and interested to jump across multiple disciplines
Team-first mentality: You are interested in building for the long-term alongside founding team members, and committed to mentoring others and being mentored
Passion for vision: Genuinely excited about our tech and its impact on accounting, finance, and economy
NYC-based: Seeking in-person environment; working from office most days of week
All-in: This is not a 9-5, we have a massive opportunity ahead of us and are looking to multiply our engineering speed. We are optimizing for the best folks and happy to compensate generously
A little something extra: You know it when you see it
Bonus points
Open-source: Contributed to open-source ML projects
Experience with financial workflows: Worked with corporate financial data/products geared to finance professionals