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Machine Learning Engineer

LocationIE-Dublin-Hanover Quay, Ireland

Work modehybrid

Typefull-time

DepartmentEngineering

Company size10,000+ people

First seen6mo ago

Last seen1d ago

About the company

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 MLE to help build industry-leading state of the art solutions. You will be leveraging text mining, deep learning, content understanding, document processing and more. You will prototype 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 Work together with the ML team to perform research, testing and evaluation of existing and emerging NLP/ML/DL methods and technologies that could be effectively applied to contractual/legal data Be knowledgeable in and be able to apply NLP techniques in order to maintain and extend the current rule-based, supervised and unsupervised methods Be knowledgeable in and able to apply ML/DL algorithms and technologies to NLP tasks such as Named Entity Recognition, POS tagging, Parsing, Sentiment Analysis, Clustering, text prediction etc. Develop an understanding of the technologies, methods and the architecture within Docusign product development. Also an understanding 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 training maintenance and enrichment process Work within the Machine Learning team to deploy models to production, using existing and emerging machine learning methods and technologies Work closely with Product Management to translate product requirements into robust, customer-agnostic machine learning success metrics 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 5+ years of experience in designing, developing, deploying and monitoring machine learning and deep learning solutions Experience programming in Python, PyTorch, TensorFlow, spaCy, scikit-learn, or equivalent machine learning framework Programming experience in one or more of the following languages - Python, C#, Java, C/C++ Bachelor’s degree in computer science, Physics, statistics, econometrics, operations research, applied mathematics or an equal computational field Preferred Demonstrated experience developing and deploying sequence-based Deep Learning models Experience in latest LLM technologies like GPT, Gemini, LLaMA etc Experience in Computer Vision Strong desire to stay ahead of industry trends and technologies with a commitment to continuous learning Experience with Machine Learning Concepts - Training, Validation, Testing, Precision/Recall, Bias/Variance etc Experience in extracting, cleansing, and manipulating large, diverse structured and unstructured sets Assist with the development of language agnostic contract clause recognition 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 [email protected]. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at [email protected] for assistance. Applicant and Candidate Privacy Notice #LI-Hybrid #LI-IC1

Requirements

Basic 5+ years of experience in designing, developing, deploying and monitoring machine learning and deep learning solutions Experience programming in Python, PyTorch, TensorFlow, spaCy, scikit-learn, or equivalent machine learning framework Programming experience in one or more of the following languages - Python, C#, Java, C/C++ Bachelor’s degree in computer science, Physics, statistics, econometrics, operations research, applied mathematics or an equal computational field Preferred Demonstrated experience developing and deploying sequence-based Deep Learning models Experience in latest LLM technologies like GPT, Gemini, LLaMA etc Experience in Computer Vision Strong desire to stay ahead of industry trends and technologies with a commitment to continuous learning Experience with Machine Learning Concepts - Training, Validation, Testing, Precision/Recall, Bias/Variance etc Experience in extracting, cleansing, and manipulating large, diverse structured and unstructured sets Assist with the development of language agnostic contract clause recognition

About the role

Docusign is looking for a passionate, talented, and inventive MLE to help build industry-leading state of the art solutions. You will be leveraging text mining, deep learning, content understanding, document processing and more. You will prototype 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 Work together with the ML team to perform research, testing and evaluation of existing and emerging NLP/ML/DL methods and technologies that could be effectively applied to contractual/legal data Be knowledgeable in and be able to apply NLP techniques in order to maintain and extend the current rule-based, supervised and unsupervised methods Be knowledgeable in and able to apply ML/DL algorithms and technologies to NLP tasks such as Named Entity Recognition, POS tagging, Parsing, Sentiment Analysis, Clustering, text prediction etc. Develop an understanding of the technologies, methods and the architecture within Docusign product development. Also an understanding 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 training maintenance and enrichment process Work within the Machine Learning team to deploy models to production, using existing and emerging machine learning methods and technologies Work closely with Product Management to translate product requirements into robust, customer-agnostic machine learning success metrics

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