Lead Applied Scientist

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, 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 the end to end AI / ML feature lifecycle by leveraging document understanding, data cleaning, data labeling, model training in machine learning, NLP, computer vision domain, offline / online evaluation techniques and more. You will be building production level machine learning models that deliver more personalized and automated customer experiences throughout the Docusign Agreement Cloud.

 

This position is an individual contributor role reporting to the Director, Machine Learning.

 

Responsibility

• Lead the team in 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 and unlock new and innovative use cases for our customers

• Be responsible for multiple initiatives, lead cross-team collaboration, plan and guide the effort of applied scientists and ML engineers on the initiatives, and shape the technical roadmap

• 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

• Be knowledgeable in and be able to build the strategy for employing the state of the art technologies to NLP tasks such as long document text understanding, entity extractions, text encoders, LLM finetuning, semantic search, question answering, query intent detection, document layout understanding, and so on

• 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

• Provide coaching and leadership in applied science for best practices, modeling and evaluation techniques, responsible AI, model interpretability and datasets enhancements

• Deliver AI products that delight customers while managing the health of the code base through continuous refactoring and management of technical debt

• Lean into leadership to deliver success against our goals and contribute to Docusign’s AI strategy and vision

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

• Minimum of 12 years of related experience with a Bachelor's degree; or 8 years of related experience with a Master's degree; or a PhD with 5 years experience; or equivalent experience

• Bachelor’s degree in Computer Science or related field

• 5+ years of experience in designing, modeling, evaluating, deploying and monitoring machine learning and deep learning solutions

• Experience as a Technical Lead managing large projects involving other Applied Scientists / ML Engineers and cross-functional partners

• 4+ years experience with deep neural networks and building NLP / NLU solutions

• 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 frameworks

Preferred

• 8+ years of experience in designing, developing, deploying and monitoring machine learning and d