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Ivo is a contract intelligence platform that uses AI to help enterprises (Meta, Uber, IBM, Intel, DoorDash, Coinbase, Shopify, Canva, Reddit, Pinterest, WordPress) solve complex contracting problems. The company recently raised Series B and has grown 800% in the last 12 months.
As a Senior AI Researcher, you will own a research roadmap end-to-end, identifying problems, designing experiments, prototyping, and shipping solutions into production. Your work will directly translate into product features that redefine how legal professionals work.
Key responsibilities:
- Advance the core AI platform by designing and implementing novel approaches to long-context legal document reasoning, contract comparison and redlining, information extraction, and automated drafting and editing.
- Make models trustworthy through research on hallucination detection and resolution, calibration, and explainability—critical in legal domains where fabricated citations can sink deals.
- Push frontier techniques into production, exploring advanced fine-tuning, PEFT, distillation, agentic systems, long-context modeling, and reasoning approaches.
- Build evaluation infrastructure: design datasets, benchmarks, and evals for measuring model performance on complex legal text; define metrics that matter.
- Ship: partner closely with Engineering and Product to move prototypes from notebook to production, write technical reports influencing platform direction, and present findings to technical and non-technical audiences.
You will work on challenging problems with high-performing colleagues who move fast and care deeply about their craft. This is not an academic role—it's a chance to see your research fundamentally change an industry.
REQUIREMENTS:
- Ph.D. in Computer Science, Engineering, Mathematics, Physics, or related quantitative field, OR equivalent industry research experience with comparable track record.
- Evidence of exceptional ability: published paper, shipped system, open-source contribution, competition result, or hard problem solved that demonstrates meaningful advantage over 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 surrounding open-source ecosystem.
- Expertise in at least one of: agentic systems, reasoning, parameter-efficient fine-tuning (PEFT), quantization, inference optimization (e.g., speculative decoding), hallucination mitigation, novel deep learning architectures, or robust LLM evaluation methodology.
- Excellent communication skills to articulate complex research findings to technical and non-technical audiences.
- Bias toward action: ship rather than perfect, measure rather than guess, prefer working prototype today over polished plan next week.
NICE TO HAVE:
- Publications at top venues (NeurIPS, AAAI, ICML, ICLR, 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.
- Track record building from zero in fast-paced startup or research environments.
