The posting
Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you'll do Docusign brings agreements to life by harnessing the power of intelligent agreement management to unlock business-critical data from documents and connect it to systems of record. Our AI Applications team within the AI Engineering organization builds ML-powered product experiences from document understanding to intelligent workflows and, increasingly, AI agents that help customers work smarter. As an MLE Intern - AI Applications, you will help design, prototype, and ship ML-driven application features, including new capabilities on our AI agent framework and document understanding features for clauses and extractions. You'll collaborate closely with applied scientists, product managers, and engineers to turn research ideas into customer-ready features in the Docusign Agreement Cloud. This is an internship role for 5 months of duration. This position is an individual contributor role reporting to the Senior Manager, Machine Learning. Responsibility Implement and iterate on ML-powered application features under the guidance of senior engineers, such as new capabilities in our AI agent framework or clause/extraction experiences in Docusign products Contribute to end-to-end ML feature workflows: data preparation, model integration, evaluation, and deployment into customer-facing experiences Integrate ML services into backend APIs and/or product surfaces, following best practices for reliability, security, and observability Build and maintain Python-based services and components that run on Kubernetes in Azure as part of our ML application stack Instrument features with logging, metrics, and basic dashboards to monitor performance and user impact Write clean, maintainable, and well-tested code, including unit and integration tests, as part of our standard development and review process Collaborate with cross-functional partners (Product, Design, QA, and other engineering teams) to clarify requirements, demo progress, and incorporate feedback Proactively learn new tools and techniques (e.g., LLMs, agent frameworks, prompt engineering, vector search, orchestration libraries) and share learnings with the team Job Designation Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation) 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. What you bring Basic Currently enrolled in a Bachelor's degree program in a relevant field with an expected graduation date between December 2027 and May/June 2028 Coursework in Computer Science, Computer Engineering, or a related technical discipline Experience in Python for backend and/or machine learning development; familiarity with another language such as C#, Java, or TypeScript/JavaScript Experience with data structures, algorithms, and core software engineering fundamentals (testing, debugging, code reviews, version control) Experience from coursework, projects, or prior internships building applications or services that consume APIs or data pipelines Ability to work from the Seattle, WA hub location in a hybrid setup (regular in-office presence) for the duration of the 12-week internship, in alignment with Docusign's intern residency and on-site work policy Preferred Previous internship or substantial project experience in software engineering, data engineering, or machine learning Academic projects or coursework involving Machine Learning, Natural Language Processing, information extraction, or document understanding Experience working with one or more ML frameworks or libraries (e.g., PyTorch, TensorFlow, scikit-learn) and associated tooling for experimentation (e.g., Jupyter, notebooks, experiment tracking) Familiarity with modern LLM and agent concepts (e.g., retrieval-augmented generation, tools/plug-ins, orchestration frameworks such as LangChain, semantic kernel, or similar) Exposure to building or integrating RESTful and/or gRPC APIs and working with JSON- or protobuf-based services Experience with version control (Git) and collaborative development workflows (code reviews, pull requests) Comfort working in a cloud-based environment, preferably Azure, and with containerization technologies like Kubernetes Strong communication skills and an interest in collaborating with cross-functional partners to deliver user-facing features Wage Transparency Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience. Based on applicable legislation, the below details pay ranges in the following locations: Washington: $38/hour - $45/hour Global benefits provide options for the following: Paid Time Off: earned time off, as well as paid company holidays based on region Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment Retirement Plans: select retirement and pension programs with potential for employer contributions Learning and Development: options for coaching, online courses and education reimbursements Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events Work Authorization Notice: Please note that we do not provide visa sponsorship or immigration support for this position. Applicants must already be authorized to work in the United States on a full-time, permanent basis without the need for current or future sponsorship. Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at [email protected]. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at [email protected] for assistance. Applicant and Candidate Privacy Notice States Not Eligible for Employment This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming. Equal Opportunity Employer It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category. EEO Know Your Rights poster #LI-Hybrid #LI-PM3
Docusign brings agreements to life by harnessing the power of intelligent agreement management to unlock business-critical data from documents and connect it to systems of record. Our AI Applications team within the AI Engineering organization builds ML-powered product experiences from document understanding to intelligent workflows and, increasingly, AI agents that help customers work smarter. As an MLE Intern - AI Applications, you will help design, prototype, and ship ML-driven application features, including new capabilities on our AI agent framework and document understanding features for clauses and extractions. You'll collaborate closely with applied scientists, product managers, and engineers to turn research ideas into customer-ready features in the Docusign Agreement Cloud. This is an internship role for 5 months of duration. This position is an individual contributor role reporting to the Senior Manager, Machine Learning. Responsibility Implement and iterate on ML-powered application features under the guidance of senior engineers, such as new capabilities in our AI agent framework or clause/extraction experiences in Docusign products Contribute to end-to-end ML feature workflows: data preparation, model integration, evaluation, and deployment into customer-facing experiences Integrate ML services into backend APIs and/or product surfaces, following best practices for reliability, security, and observability Build and maintain Python-based services and components that run on Kubernetes in Azure as part of our ML application stack Instrument features with logging, metrics, and basic dashboards to monitor performance and user impact Write clean, maintainable, and well-tested code, including unit and integration tests, as part of our standard development and review process Collaborate with cross-functional partners (Product, Design, QA, and other engineering teams) to clarify requirements, demo progress, and incorporate feedback Proactively learn new tools and techniques (e.g., LLMs, agent frameworks, prompt engineering, vector search, orchestration libraries) and share learnings with the team
Basic Currently enrolled in a Bachelor's degree program in a relevant field with an expected graduation date between December 2027 and May/June 2028 Coursework in Computer Science, Computer Engineering, or a related technical discipline Experience in Python for backend and/or machine learning development; familiarity with another language such as C#, Java, or TypeScript/JavaScript Experience with data structures, algorithms, and core software engineering fundamentals (testing, debugging, code reviews, version control) Experience from coursework, projects, or prior internships building applications or services that consume APIs or data pipelines Ability to work from the Seattle, WA hub location in a hybrid setup (regular in-office presence) for the duration of the 12-week internship, in alignment with Docusign's intern residency and on-site work policy Preferred Previous internship or substantial project experience in software engineering, data engineering, or machine learning Academic projects or coursework involving Machine Learning, Natural Language Processing, information extraction, or document understanding Experience working with one or more ML frameworks or libraries (e.g., PyTorch, TensorFlow, scikit-learn) and associated tooling for experimentation (e.g., Jupyter, notebooks, experiment tracking) Familiarity with modern LLM and agent concepts (e.g., retrieval-augmented generation, tools/plug-ins, orchestration frameworks such as LangChain, semantic kernel, or similar) Exposure to building or integrating RESTful and/or gRPC APIs and working with JSON- or protobuf-based services Experience with version control (Git) and collaborative development workflows (code reviews, pull requests) Comfort working in a cloud-based environment, preferably Azure, and with containerization technologies like Kubernetes Strong communication skills and an interest in collaborating with cross-functional partners to deliver user-facing features
