Machine Learning Engineer

Company Overview

Docusign helps agreements come to life for more than 1.5 million customers and over a billion users across 180+ countries. Its intelligent agreement management platform turns document data into actionable business information, helping organizations streamline processes and reduce time, cost, and missed opportunities. Docusign is known globally for its e-signature and contract lifecycle management solutions.

Role Summary

The company is hiring a Machine Learning Engineer to design and prototype advanced machine learning solutions that improve personalization and automation across the Docusign Agreement Cloud. This role focuses on text mining, deep learning, content understanding, and document processing. The position is an individual contributor role reporting to the Director of Machine Learning.

Key Responsibilities

• Partner with the ML team to research, test, and evaluate current and emerging NLP, ML, and deep learning approaches for contractual and legal data.
• Apply natural language processing methods to extend and maintain both rule-based and supervised/unsupervised systems.
• Use machine learning and deep learning techniques for NLP tasks such as named entity recognition, part-of-speech tagging, parsing, sentiment analysis, clustering, and text prediction.
• Build a solid understanding of Docusign’s product architecture, development practices, software delivery flow, and release management process.
• Support the existing model training, maintenance, and enrichment workflow, and help improve it where needed.
• Work with the ML team to move models into production using modern machine learning methods and tools.
• Collaborate with Product Management to convert product needs into reliable, customer-neutral machine learning success metrics.

Requirements

• At least 5 years of experience building, deploying, and monitoring machine learning and deep learning solutions.
• Hands-on programming experience with Python and ML frameworks such as PyTorch, TensorFlow, spaCy, scikit-learn, or similar tools.
• Programming knowledge in one or more of Python, C#, Java, or C/C++.
• Bachelor’s degree in computer science, physics, statistics, econometrics, operations research, applied mathematics, or a similar quantitative field.
• Preferred experience includes sequence-based deep learning models.
• Familiarity with modern LLM technologies such as GPT, Gemini, or LLaMA.
• Exposure to computer vision.
• Strong interest in staying current with industry trends and a commitment to ongoing learning.
• Working knowledge of machine learning concepts such as training, validation, testing, precision/recall, and bias/variance.
• Ability to extract, clean, and work with large structured and unstructured datasets.
• Bonus experience supporting language-agnostic contract clause recognition.

Work Arrangement

This is a hybrid position. Employees split time between the office and remote work, with access to an office required. The expected cadence is at least 2 in-office days per week, though this may vary by team. Job designations at Docusign can be In Office, Hybrid, or Remote depending on the role, and these may change based on business needs and local law.

Culture and Values

Docusign emphasizes trust, honesty, equal opportunity, collaboration, and open exchange of ideas. The company aims to create meaningful work while building a more agreeable world for employees, customers, and communities.

Accommodation and Support

Docusign provides reasonable accommodations for qualified individuals with disabilities during the application process. Religious accommodations are also available upon request. If you need help with the application process or run into technical issues, you can contact the talent operations team for assistance.

Privacy Notice

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