Senior machine learning engineer — legal language models
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Job Description
Own the models behind ZAAN Contract Review: the systems that read a contract against a firm's playbook, rank every issue by severity and propose a redline a partner would sign off. You will take models from evaluation set to production at the precision legal work demands. What you will do Fine-tune, distil and serve large language models for clause classification, risk scoring and redline generation across 38 languages. Build retrieval over playbooks and precedent so every flag cites the clause and the deal it came from. Design offline and online evaluation with lawyers in the loop: precision/recall per clause type, citation faithfulness, regression gates in CI. Cut latency and cost per document without losing accuracy: batching, quantisation, speculative decoding, caching. Work with our security team so customer data never trains shared models and stays in the region the customer chose. What you bring 5+ years building ML systems that run in production, including recent hands-on work with transformer LLMs. Strong Python and Py Torch; experience with at least one serving stack (v LLM, Tensor RT-LLM, TGI or similar). Rigour about evaluation: you design test sets, measure error by category and can explain why a model fails. Clear written English. Legal, financial or other high-stakes domain experience is a strong plus. Nice to have Long-context modelling, structured output / constrained decoding, multilingual NLP, especially German, French or Chinese. Experience with preference optimisation (DPO, RLHF) on expert feedback. How we hire A 10-minute AI interview in English (you are told up front that you are speaking with an AI), a conversation with the team you would join, and a short paid practical task that mirrors real work. We aim to decide within three weeks.
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