Software Engineer, Harvey
ML, Document Processing
$180-280k
+ Equity
Generative AI for legal teams
Job no longer available
Generative AI for legal teams
201-500 employees
Job no longer available
$180-280k
+ Equity
201-500 employees
Company mission
To help build the future of professional services.
Role
Who you are
- The ideal candidate for this role has strong backend fundamentals (distributed systems, data processing) and experience in building production systems that require experimentation
- We’re looking for someone who is hands-on and execution-focused in their approach to experimentation - you get things done and can navigate trade-offs between precision, cost, and speed
- 3+ YoE (post-BS/MS) in an engineering or research role
- Demonstrated experience working cross-functionally with other engineering teams: you’ll need to prioritize investment in processing quality based on our product needs
- Experience with using a data-driven approach to guide engineering decisions, like recommendation engines or LLM providers
- Experience with search infrastructure or vector databases is a plus
- Track record of shipping reliable products and a strong attention to detail
- Grit - experience working at early-stage startups is a plus
What the job involves
- In this role, you will build at the boundary of what is possible in document understanding and incorporate new advancements in OCR, semantic chunking, and vector storage into Harvey’s core system
- Design and build a robust evaluation system for document understanding. Build and extend our large set of complex documents, like handwritten text from decades-old governing law or large Excel files containing the complex calculations of a corporate merger. Establish reliable baseline labels by working with legal domain experts or leveraging synthetic labeling
- Iterate on representation schemes for different data types: what’s the best way to represent a spreadsheet cell in a retrieval database? How should models treat strike-throughs?
- Benchmark and implement modern advancements across various modalities, like vision and audio models, into the Harvey stack
- Improve the scalability, observability, and fault tolerance of our document processing service
Our take
The explosive popularity of generative AI tools has seen specialized solutions popping up for all kinds of industries. Hoping to help supercharge efficiency and productivity for legal teams, Harvey supplies Gen AI that can assist with documentation, as well as aid research and optimize workflows.
Via natural language instructions, Harvey helps draft and analyze legal documents. It can also answer complex questions across large document sets, or even handle research queries that cover multiple domains in legal, regulatory and tax.
Its ability to support legal practitioners as if it's another member of the team is what makes Harvey particularly interesting. This approach has seen the company raise substantial funding, reaching Unicorn status in 2024. Funds will be used to expand to new geographies, grow headcount and further collect and curate data to train more “domain-specific” AI models.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 7 rounds)
Jun 2025
$300m
SERIES E
Feb 2025
$300m
SERIES D
Total funding: $806.1m
Company benefits
- Comprehensive health, dental and vision coverage
- Retirement benefits (401k match up to 4%)
- Flexible PTO
Company HQ
SoMa, San Francisco, CA
Leadership
Winston Weinberg
(CEO)Graduated with a Juris Doctor from the USC Gould School of Law, then spent 1 year as an Associate at O'Melveny & Myers before founding Harvey.
Gabe Pereyra
(President)Previously worked as a Research Scientist at Meta and DeepMind. Also spent a year as a Brain Resident at Google.
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