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
Hybrid:
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.
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
Working here
Accommodation
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