AI Engineer/Research

Automates data intake and service delivery process for tax firms.
$125,000 - $250,000
Machine Learning
Senior Software Engineer
Hybrid
11 - 50 Employees
6+ years of experience
AI · Enterprise SaaS

Description For AI Engineer/Research

Soraban is a post-PMF B2B startup focused on automating data intake and service delivery processes for tax firms. They're experiencing exponential monthly ARR growth and are looking for an AI Research Engineer to scale their AI products. The role will initially be remote but transition to in-person within 3-6 months at their locations in San Francisco, Austin, or Tempe.

The ideal candidate should have strong experience in LLM technologies, transformer architectures, and modern ML stack. They value self-starters who can work autonomously and have a proven track record of shipping products end-to-end. The company is particularly interested in candidates with experience in Ruby on Rails and those who have worked directly with founders before.

Soraban's interview process is streamlined and typically takes 14 days, consisting of a quick phone screen, technical screen over Zoom, and then an offer. They're building software to help accountants automate their client data intake process, with plans to develop a Copilot for accountants.

The company, founded in 2021, has a team of around 30 people and offers competitive compensation including both salary and equity components. They're looking for ambitious individuals who can contribute to building the best software solution for accountants and can handle the fast-paced environment of a growing startup.

Last updated 4 hours ago

Requirements For AI Engineer/Research

Python
Ruby
  • At least 5 years of full-time experience as a software engineer
  • Strong curiosity and willingness to learn new things
  • Experience working with LLM, such as Anthropic, LLAMA, Open AI, or similar
  • Understanding Transformer Architecture
  • Experience with LLM tuning, prompt engineering, instruction tuning, RLHF
  • Experience with embeddings, and tools like langchain, pinecone
  • Experience with the modern ML stack (e.g., TF2, Jax, TPUs)
  • Experience scraping and incorporate data at scale

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