Applied Science Intern

Docusign • San Francisco, CA

23h • Hybrid

About The Position

Docusign is seeking a post-graduate student or recent graduate for a 10-to-12-week summer internship, described as three months in duration. The intern will work with scientists and engineers to apply advanced mathematical, statistical, and machine learning techniques to complex problems with practical product and customer impact. Projects may involve document understanding, such as automated clause extraction, semantic risk detection, and structural analysis, or intelligent AI agents that orchestrate agreement workflows. The intern will own a high-impact project from conception through prototyping, working with large datasets, modern technologies, and collaborative agile workflows. This is an individual contributor role reporting to the Senior Manager, Applied Science.

The position is hybrid, requiring access to an office and at least two in-office days per week; frequency may vary by team, with a weekly in-office expectation. California compensation is listed at $63–$80 per hour, depending on location and job-related knowledge, skills, and experience. Applicants must already be authorized to work in the United States permanently without current or future sponsorship. The role is not eligible for employment in Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia, or Wyoming.

Requirements

• Currently enrolled in, or a recent graduate of, a Master's or PhD program in Computer Science, Data Science, Operations Research, Statistics, Applied Mathematics, Physics, or a highly quantitative engineering field.
• Experience with at least one core programming language, such as Python, Rust, C++, or Java.
• Experience with data structures, algorithms, and core machine learning concepts such as regression, classification, and clustering.
• Experience querying and manipulating data using SQL or data-frame libraries such as Pandas.
• Must already be authorized to work in the United States on a full-time, permanent basis without current or future visa sponsorship.

Nice To Haves

• Practical experience or coursework in Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, or Optimization.
• Familiarity with machine learning libraries and frameworks such as PyTorch, TensorFlow, Scikit-Learn, or JAX.
• Experience with distributed computing frameworks such as Apache Spark or Hadoop, or cloud-based data warehouses such as AWS, Google Cloud, or Azure.
• Peer-reviewed publications in leading scientific conferences or journals, such as NeurIPS, ICML, KDD, or CVPR, or a strong portfolio of open-source contributions.
• Exceptional verbal and written communication skills and the ability to explain complex technical concepts to diverse audiences.

Responsibilities

• Design, develop, and evaluate novel algorithms and statistical models to address complex business and technical challenges.
• Analyze and manipulate large-scale structured and unstructured datasets to extract insights and develop model features.
• Partner with Product Managers and Software Engineering teams to turn theoretical concepts into functional, scalable prototypes.
• Design and conduct evaluation frameworks, including offline simulations and controlled A/B experiments, to assess model performance, identify edge cases, and evaluate statistical significance.
• Document methodology, findings, and code, and present project outcomes to technical and non-technical stakeholders at the conclusion of the internship.

What This Job Offers

• Career Level: Intern