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 Machine Learning engineer 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 computer vision, 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 of Docusign. Responsibility Work together with your 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 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 Apply computer vision for document understanding tasks such as layout and object detection, image classification and tagging 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 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 of experience, or equivalent experience Experience in designing, developing, deploying 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 Preferred Demonstrated experience developing and deploying large scale document understanding models in production Hands-on experience building multi-modal solutions between CV or 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 and technologies with a commitment to continuous learning Extensive experience in data collecting, 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 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 #LI-Hybrid #LI-IC1
Lead Machine Learning Engineer
DocuSign · Enterprise · Dublin, Ireland · Engineering
Lead Machine Learning Engineer at DocuSign, focusing on building and deploying production-level AI/ML solutions for document understanding, leveraging computer vision and NLP. The role involves the full ML lifecycle, from research and development to deployment and monitoring of models within the Docusign Agreement Platform.
What you'd actually do
- Work together with your 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
- 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
- Apply computer vision for document understanding tasks such as layout and object detection, image classification and tagging
- 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
Skills
Required
- Experience in designing, developing, deploying and monitoring machine learning and deep learning solutions
- 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
- 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
Nice to have
- Experience developing and deploying large scale document understanding models in production
- Hands-on experience building multi-modal solutions between CV or NLP
- Extensive experience in data collecting, cleaning, sampling, and processing large, diverse structured or unstructured datasets
What the JD emphasized
- production-level machine learning models
- deploy models into production
- build scalable AI systems
- online inferencing processes
- document understanding models in production
- multi-modal solutions
Other signals
- building production-level machine learning models
- deploying models into production
- build scalable AI systems