Senior Applied ScientistFull time
DocuSign helps organizations connect and automate how they agree. Our flagship product, eSignature, is the world’s #1 way to sign electronically on practically any device, from virtually anywhere, at any time. Today, more than a million customers and a billion users in over 180 countries use DocuSign to accelerate the process of doing business and simplify people’s lives.
What you’ll do
DocuSign is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading state of the art AI/ML solutions. You will be able to get your hands on all aspects of the AI /ML feature life cycle by leveraging your expertise in NLP and document understanding. You will be building production-level machine learning models that deliver more personalized and automated customer experiences throughout the DocuSign Agreement Platform.
This position is an individual contributor role reporting to the Director, Machine Learning.
- Work together with your Applied Science team to perform model development, research, testing, and evaluation of existing and emerging deep learning methods and technologies that can be effectively applied to the contract domain
- Be knowledgeable in and able to apply the latest architectures and technologies to build DocuSign IP and solve complex NLP challenges including, but not limited to, generating representations, text understanding, semantic retrieval, contextual extractions, summarization
- Develop an understanding of the technologies, methods and the architecture within DocuSign product development Understand, assist, and improve the existing model training, evaluation, and online inferencing processes, define online metrics, and design user feedback 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 designs and plans for robust, customer-agnostic machine learning solutions
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
- Minimum of 5 years of related experience with a Bachelor’s degree; or 3 years related experience with a Master’s degree; or a PhD without experience; or equivalent experience
- Experience in designing, developing, and monitoring machine learning and deep learning solutions
- Experience programming in PyTorch, TensorFlow, or equivalent deep learning framework
- Fluent in Python
- Bachelor’s degree in computer science, physics, statistics, econometrics, operations research, applied mathematics or an equal computational field
- Demonstrated experience developing and deploying large scale document understanding models in production
- Hands-on experience building multi-modal solutions between CV and NLP
- Experience in latest NLP techniques including LLMs and language representations.
- Experience in text extraction techniques, especially using OCR and direct extraction from docx, images, and pdfs
- Strong desire to stay ahead of industry trends & technologies with a commitment to continuous learning
- Extensive experience in data collecting, cleaning, sampling, and processing large, diverse structured or unstructured datasets
Based on applicable legislation, the below details pay ranges in the following locations: California: $146,800 - $235,025 base salary Washington and New York (including NYC metro area): $139,800 - $207,325 base salary
This role is also eligible for bonus, equity and benefits.
San Francisco, California; Seattle, Washington