Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you'll do Docusign is looking for a passionate and experienced Engineering Manager to lead a team of machine learning engineers in building industry-leading state-of-the-art AI/ML solutions. You will guide your team through all aspects of the AI/ML feature life cycle, leveraging expertise in NLP and document understanding. You will be responsible for overseeing the development and deployment of production-level machine learning models that deliver more personalized and automated customer experiences throughout the Docusign Agreement Platform. This position is a people manager role reporting to the Director, Machine Learning. Responsibility Lead and mentor a team of machine learning engineers and software engineers in model development, deployment, testing, and evaluation of existing and emerging deep learning methods and technologies that can be effectively applied to the contract domain Guide the team in applying the latest architectures and technologies to build Docusign IP and solve complex NLP challenges including, but not limited to, generating representations, text understanding, semantic retrieval, contextual extractions, and summarization Foster a deep understanding within the team of the technologies, methods, and architecture within Docusign product development Define, improve, and assist the team with existing model training, evaluation, and online inferencing processes, establish online metrics, and design user feedback mechanisms for our AI/ML features Collaborate closely with engineering partners to deploy models into production, build scalable AI systems, and monitor and improve performance metrics Work closely with Product Management to translate user scenarios and product requirements into designs and plans for robust, customer-agnostic machine learning solutions Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law. What you bring Basic Bachelor’s degree in computer science, physics, statistics, econometrics, operations research, applied mathematics or an equal computational field 6+ years of relevant professional experience, including 2+ years leading and managing machine learning engineering teams Experience with direct LLM development including large-scale pre-training, supervised fine-tuning (SFT), parameter-efficient fine-tuning (e.g., LoRA, QLoRA), and model evaluation, not limited to prompt engineering or inference Experience deploying and maintaining LLMs in production environments, including model evaluation, versioning, and performance monitoring Experience LLM architectures, tokenization, attention mechanisms, prompt engineering, and transfer learning Experience with standard processes for optimizing LLM performance, efficiency, safety, and alignment Preferred Master's or PhD in a relevant computational field Hands-on experience across the broader NLP stack, including dense and sparse embeddings, semantic search, named entity recognition, text classification, information extraction, and retrieval-augmented generation (RAG) Experience in text extraction techniques, especially using OCR and direct extraction from docx, images, and pdfs Strong desire to stay ahead of industry trends & technologies with a commitment to continuous learning Extensive experience in data collecting, cleaning, sampling, and processing large, diverse structured or unstructured datasets Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relation