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).

Docusign is looking for a passionate, versatile, and inventive Senior Applied Scientist to help build industry-leading groundbreaking AI/ML solutions. You will be able to get your hands on the end to end AI/ML feature lifecycle by applying data labeling and document understanding, machine learning across NLP, computer vision and multi-modal techniques including LLMs and agentic approaches, offline and online evaluation techniques, and more. You will be building production-level machine learning models that deliver more personalized and automated customer experiences throughout Docusign's new Intelligent Agreement Management (IAM) platform.

This position is an Individual Contributor role reporting to the Manager, Applied Science.

Responsibility

• Work together with your Applied Science team to perform model development, research, testing and evaluation of existing and emerging NLP/ML/DL methods and models (incl. open source and licensed LLMs) that could be effectively applied to the contract domain

• Be knowledgeable in and be able to apply the latest architectures and technologies to NLP tasks such as Named Entity Recognition, Content extractions, Search and Question Answering, Query intent detection and action formulation, Document layout understanding, and others

• Develop an understanding of the technologies, methods and the architecture within Docusign product development, and of the entire software development end-to-end process as well as the product code and release management process will be essential

• Understand, assist and improve the existing model training, evaluation and online inferencing process, define online metrics and design user feedback loop for our AI/ML features

• Work closely with the engineering partners to deploy models into production, build scalable AI systems, monitor and improve performance metrics

• Work closely with Product Management to translate user scenarios and product requirements into robust, customer-agnostic machine learning solutions, participate in design and planning discussions to make sure we can deliver high quality AI/ML features on time

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.

Basic

• 8+ years of related experience with a Bachelor’s degree; or 6+ years related experience with a Master’s degree; or a PhD with 3+ years experience; or equivalent experience
• Experience in designing, developing, deploying and monitoring machine learning and deep learning solutions
• Hands-on experience working with the latest NLP models like BERT, SentenceBert and LLMs like GPT, Gemini, Llama families of models, etc.
• Experience programming in Python, PyTorch or TensorFlow, spaCy, scikit-learn, or equivalent machine learning framework
• Bachelor’s degree in computer science, Physics, statistics, applied mathematics or an equivalent computational field

Preferred

• Demonstrated experience developing and deploying large scale NLP and deep learning based models in production
• Extensive experience in data collection, cleaning, sampling, and processing large, diverse structured or unstructured datasets.
• Familiarity with RAG and LLM agentic approaches is a plus
• Experience in Computer Vision techniques, especially in document layout analysis, OCR, and familiarity with vision transformer based models is a plus
• Experience in multilingual LLM pretraining or fine-tuning work is a plus
• Strong desire to stay ahead of industry trends technologies with a commitment to continuous learning

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:

California: $X/hour - $X/hour or $X - $X base salary

Illinois and Colorado: $X/hour - $X/hour or $X - $X base salary

Washington, New Jersey and New York (including NYC metro area): $X/hour - $X/hour or $X - $X base salary

Washington DC: $X/hour - $X/hour or $X - $X base salary

This role is also eligible for the following:

• Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
• Stock: This role is eligible to receive Restricted Stock Units (RSUs).

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

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 accommodations@docusign.com.

If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance.

Applicant and Candidate Privacy Notice

This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming.

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.

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