Machine Learning Engineer

DocuSign, Inc.; United States; Hybrid; USD 130,000 - 170,000; Full time

Benefits offered by this job

Hybrid work arrangement

Office in United States

Flexible schedule

Job summary

DocuSign, Inc. seeks an experienced ML/NLP engineer to build text mining, document understanding, and automation for contractual content on a large-scale platform.

This individual contributor role blends applied NLP research with hands-on model development and deployment, shaping customer experiences while collaborating with product and engineering teams. Hybrid work with in-office presence required.

Qualifications

• 5+ years designing, developing, deploying, and monitoring ML/DL solutions.
• Experience with Python and ML frameworks (PyTorch, TensorFlow, spaCy, scikit-learn).
• Programming experience in Python, C#, Java, or C/C++.
• Bachelor’s degree in a computing/quantitative field.
• Understanding ML concepts: training/validation, precision/recall, bias-variance.
• Experience handling large structured and unstructured data.

Responsibilities

• Investigate NLP, ML, and DL techniques for contractual data.
• Maintain and extend language-processing methods.
• Apply NER, POS tagging, parsing, sentiment analysis, clustering, text prediction.
• Learn product architecture and release processes.
• Support and improve training-data workflows.
• Deploy models to production and measure impact with product teams.

Skills

NLP research

ML deployment

Python

C#

Java

C/C++

PyTorch

TensorFlow

spaCy

scikit-learn

Model deployment

Data wrangling

Education

Bachelor’s degree in computer science or related computational field

Tools

PyTorch

TensorFlow

spaCy

scikit-learn

Job description

Role overview

Build machine learning capabilities for text mining, document understanding, and automation of contractual and legal content. This individual contributor position combines applied NLP research with hands‑on model development and deployment, helping create more personalized and efficient customer experiences across a large-scale agreement platform.

Responsibilities

• Investigate and evaluate NLP, machine learning, and deep learning techniques that can be applied to contractual and legal data.
• Maintain and extend rule-based, supervised, and unsupervised language‑processing methods.
• Apply approaches such as named entity recognition, part‑of‑speech tagging, parsing, sentiment analysis, clustering, and text prediction.
• Learn and work within the product architecture, software development lifecycle, codebase, and release‑management processes.
• Support and improve training‑data maintenance and enrichment workflows.
• Deploy models to production and collaborate with product management on meaningful, customer‑agnostic success metrics.

Requirements

• 5+ years designing, developing, deploying, and monitoring machine learning or deep learning solutions.
• Experience with Python and tools such as PyTorch, TensorFlow, spaCy, scikit‑learn, or equivalent frameworks.
• Programming experience in Python, C#, Java, C/C++, or a comparable language.
• Bachelor’s degree in computer science, physics, statistics, econometrics, operations research, applied mathematics, or a related computational field.
• Understanding of training, validation, testing, precision and recall, bias‑variance, and other core machine learning concepts.
• Experience extracting, cleaning, and manipulating large, diverse structured and unstructured datasets.

Nice to have

• Experience with sequence‑based deep learning, modern large language models, or computer vision.
• Interest in continuous learning and keeping pace with advances in machine learning.
• Experience supporting language‑agnostic contract clause recognition.

Benefits and work setup

Hybrid role requiring access to an office, with a weekly in‑office expectation of at least two days, subject to team and local requirements.