Company Overview

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.

• 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

What You Bring

• 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

• 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