Applied Scientist

Docusign Partners; Toronto; Hybrid; CAD 80,000 - 120,000; Full time

Job summary

Docusign is seeking an Applied Scientist to advance AI/ML solutions within their Intelligent Agreement Management platform. The role involves model development, testing, and deployment focusing on NLP and document understanding technologies. Applicants should have a strong foundation in machine learning and fluent programming skills in Python, with experience in frameworks like PyTorch and TensorFlow.

Benefits

Flexible work schedule

Career development opportunities

Commitment to diversity and inclusion

Qualifications

• 2+ years related experience or equivalent education.
• Experience programming in machine learning frameworks.
• Fluent in Python.

Responsibilities

• Develop and deploy machine learning models for document understanding.
• Collaborate with teams on model evaluation and testing.
• Translate product requirements into machine learning solutions.

Skills

NLP

Machine Learning

Deep Learning

Python

Education

Bachelor’s degree in computer science, physics, statistics or equivalent

Tools

PyTorch

TensorFlow

Job description

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 is looking for a passionate, versatile, and inventive Applied Scientist to help build industry-leading, groundbreaking AI/ML solutions. You will be able to get your hands on all aspects of the AI/ML feature life cycle by applying 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 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 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, 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
  
  

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

• 2+ years of related experience with a Bachelor’s degree; or 1+ 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 an equivalent deep learning framework
• Experience in the latest NLP techniques including LLMs and language representations
• Fluent in Python
• Bachelor’s degree in computer science, physics, statistics, econometrics, operations research, applied mathematics or an equivalent computational field
  
  

Preferred

• Demonstrated experience developing and deploying large scale document understanding models in production
• 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 collection, cleaning, sampling, and processing large, diverse structured or unstructured datasets
  
  

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 [e-mail].

If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at [e-mail] for assistance.

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