Engineering at Ivo

Engineers at Ivo are inventors. Ivo was first-to-market with:

An AI agent that lives in MS Word and edits the document for you [2023]
Ditching imprecise embeddings models in favor of agentic RAG [2023]
Large-scale LLM-based legal fact extraction [2024]
A legal assistant that can search large contract databases without sacrificing accuracy [2024]
Clustering legal documents descended from the same family [2025]
Automatic deviation analysis to locate buried risk in huge contract databases [2025]
Merging contracts with their amendments to produce a time series of "composite"
contracts (a customer actually cried when we showed her this) [2025]

The Role: Why, What, and Who

Why

AI Researchers are the engine of innovation at Ivo. You'll push the state of the art in applying LLMs, deep learning, and advanced AI techniques to the unique and high-stakes challenges of the legal domain — where accuracy, explainability, and robustness aren't nice-to-haves, they're the product. Your research will translate directly into features that redefine how legal professionals work.

This isn't an academic role. It's a chance to see your research fundamentally change an industry.

What you'll do

You'll own a research roadmap end-to-end: identifying the right problems, designing experiments, prototyping, and shipping the winners into production alongside the engineering team. Concretely, that looks like:

Advance the core AI platform. Design and implement novel approaches to the problems at the heart of Ivo's product: reasoning over long-context legal corpora, contract comparison and redlining, information extraction, and automated drafting and editing.

Make our models trustworthy. Conduct research on procedural hallucination detection and resolution, calibration, and explainability. In a domain where a single fabricated citation can sink a deal, the bar for groundedness is uncompromising — your job is to keep raising it. Push frontier techniques into production. Explore and apply advanced fine-tuning, PEFT, and distillation techniques to make our models faster, cheaper, and more accurate on legal- specific tasks. Evaluate emerging work in agentic systems, long-context modeling, and reasoning, and figure out which ideas actually move the needle for our customers.

Build the evaluation infrastructure. Design and maintain datasets, benchmarks, and evals for training and measuring model performance on complex legal text. Define the metrics that matter, and hold the team to them.

Ship. Partner closely with Engineering and Product to take prototypes from notebook to production, write internal reports that influence the technical direction of the platform, and present findings to both technical and non-technical audiences across the company.

Who you are

Required:

A Ph.D. in Computer Science, Engineering, Mathematics, Physics, or a related
quantitative field — or equivalent industry research experience with a comparable track
record.
Evidence of exceptional ability — a paper, shipped system, open-source contribution,
competition result, or hard problem you cracked that puts you meaningfully ahead of
your peers.
Deep, hands-on experience in deep learning research and development, particularly with
LLMs. Strong working knowledge of modern frameworks (PyTorch, JAX, or TensorFlow)
and the surrounding open-source ecosystem.
Expertise in at least one of: agentic systems, reasoning, parameter-efficient fine-tuning
(PEFT) methods, quantization, inference optimization (e.g., speculative decoding),
hallucination mitigation, novel architectures in deep learning, or robust evaluation
methodology for LLMs.
Excellent communication skills, with the ability to articulate complex research findings
clearly to both technical and non-technical audiences.
A bias toward action: you ship rather than perfect, you measure rather than guess, and
you'd rather have a working prototype today than a polished plan next week.

Nice to have:

Publications at top venues — e.g., ML/AI conferences (NeurIPS, AAAI, ICML, ICLR), or
peer-reviewed journals in adjacent quantitative fields (Journal of Computational Physics,
SIAM journals, Journal of the ACM, Nature, Science, PNAS) — or equivalent strong
research contributions in industry.
Experience with long-context modeling, retrieval, or grounded generation in high-stakes
domains (legal, medical, financial).
Prior work on hallucination detection, calibration, or interpretability.
A track record of building from zero in fast-paced startup or research environments.
You'll thrive at Ivo if
You love writing code, but you love impact more. We're a team of engineers at heart,
but our #1 goal is the best possible product. That means making pragmatic choices and
looking for 80/20 solutions over the elegant 100% answer.
You're relentlessly resourceful. When the path isn't clear, you find one. When the tool
doesn't exist, you build it.
You have a strong internal sense of urgency. You'd rather do it today than tomorrow.
You're excited by the adventure of building a company. Startup experience is
preferred, but not required — the disposition matters more than the resume line.

Mission

Every major business has an in-house legal team, and all of those lawyers are overworked. 80- hour weeks, tight deadlines, and contract-reading death marches are the industry norm. Until recently, there wasn't anything technology could do about it.

LLMs have given us the ability to give lawyers their lives back. At Ivo, that's our mission. We're building an AI-native platform to automate legal drudgery. People love our software —despite high competition, we have the highest trial win rate on the market (85%). We're genuinely improving people's lives, and we're only just getting started.

FAQ

How far along are we? We launched in early access in 2023. Since then, we've had an incredible response from the market and are growing rapidly. We 6x'd ARR in the last 12 months. Our clients include Uber, Reddit, IBM, Canva, Pinterest, WordPress, and more. We're happy to share more details with candidates who go through our interview process.
Can I work remotely? We have an in-office culture, with some hybrid flexibility.
Compensation: The USD salary range for this role is $250K–$325K. Final offer amounts are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above.

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