Manager, Machine Learning Engineering
Docusign · Dublin, County Dublin, Ireland
- On site
- Full-time
- $180,000 / year
- Dublin, County Dublin, Ireland
Job highlights
- Lead machine learning engineers building AI/ML solutions.
- Develop production ML models for customer experience.
- Oversee LLM development and deployment lifecycles.
- Collaborate with Product Management on ML features.
- Focus on NLP and document understanding applications.
About the role
About Docusign
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 and experienced Engineering Manager to lead a team of machine learning engineers in building industry-leading state-of-the-art AI/ML solutions. You will guide your team through all aspects of the AI/ML feature life cycle, leveraging expertise in NLP and document understanding. You will be responsible for overseeing the development and deployment of production-level machine learning models that deliver more personalized and automated customer experiences throughout the Docusign Agreement Platform. This position is a people manager role reporting to the Director, Machine Learning.Responsibility
- Lead and mentor a team of machine learning engineers and software engineers in model development, deployment, testing, and evaluation of existing and emerging deep learning methods and technologies that can be effectively applied to the contract domain.
- Guide the team in applying 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, and summarization.
- Foster a deep understanding within the team of the technologies, methods, and architecture within Docusign product development.
- Define, improve, and assist the team with existing model training, evaluation, and online inferencing processes, establish online metrics, and design user feedback mechanisms for our AI/ML features.
- Collaborate closely with engineering partners to deploy models into production, build scalable AI systems, and 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- Bachelor’s degree in computer science, physics, statistics, econometrics, operations research, applied mathematics or an equal computational field
- 6+ years of relevant professional experience, including 2+ years leading and managing machine learning engineering teams
- Experience with direct LLM development including large-scale pre-training, supervised fine-tuning (SFT), parameter-efficient fine-tuning (e.g., LoRA, QLoRA), and model evaluation, not limited to prompt engineering or inference
- Experience deploying and maintaining LLMs in production environments, including model evaluation, versioning, and performance monitoring
- Experience LLM architectures, tokenization, attention mechanisms, prompt engineering, and transfer learning
- Experience with standard processes for optimizing LLM performance, efficiency, safety, and alignment
- Master's or PhD in a relevant computational field
- Hands-on experience across the broader NLP stack, including dense and sparse embeddings, semantic search, named entity recognition, text classification, information extraction, and retrieval-augmented generation (RAG)
- 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
Life at Docusign
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
Key skills/competency
- Machine Learning Engineering
- AI/ML Solutions
- NLP
- Document Understanding
- Deep Learning
- LLM Development
- Production Deployment
- Model Training & Evaluation
- Scalable AI Systems
- Product Management
Skills & topics
- Machine Learning Engineering
- AI
- ML
- NLP
- Deep Learning
- LLM
- Manager
- Engineering Manager
- Docusign
- Hiring
How to get hired
- Tailor your resume: Highlight your experience in LLM development, production deployment, and team leadership, aligning it with Docusign's focus on AI/ML and NLP solutions.
- Showcase leadership: Emphasize your proven ability to mentor and manage machine learning engineering teams, detailing your experience in guiding projects from inception to deployment.
- Demonstrate technical expertise: Detail your hands-on experience with LLM architectures, fine-tuning techniques (SFT, LoRA), and production maintenance, including evaluation and monitoring.
- Understand Docusign's mission: Research Docusign's commitment to intelligent agreement management and how AI/ML drives their customer experience and business objectives.
Technical preparation
Deep dive into LLM architectures and fine-tuning.,Practice deploying and monitoring ML models in production.,Study NLP techniques and document understanding.,Review advanced deep learning methods and evaluation.
Behavioral questions
Describe leading and mentoring ML engineering teams.,How have you translated product needs into ML solutions?,Share an example of a challenging NLP problem solved.,Discuss your approach to fostering team understanding of tech.
Frequently asked questions
- What is the work arrangement for the Machine Learning Engineering Manager role at Docusign?
- This is a Hybrid position. Employees are expected to divide their time between in-office and remote work, with a minimum of two days per week in the office. Access to an office location is required.
- What are the core responsibilities of a Machine Learning Engineering Manager at Docusign?
- The Machine Learning Engineering Manager will lead a team of ML engineers in developing and deploying state-of-the-art AI/ML solutions, focusing on NLP and document understanding for the Docusign Agreement Platform. Responsibilities include model development, deployment, team mentorship, and collaboration with Product Management.
- What specific LLM experience is required for this Machine Learning Engineering Manager position?
- The role requires direct LLM development experience, including large-scale pre-training, supervised fine-tuning (SFT), parameter-efficient fine-tuning (e.g., LoRA, QLoRA), model evaluation, and deploying/maintaining LLMs in production environments. Familiarity with LLM architectures, tokenization, and prompt engineering is essential.
- What kind of technical background is preferred for the Machine Learning Engineering Manager role?
- While a Bachelor's degree in a computational field is basic, a Master's or PhD in a relevant field is preferred. Hands-on experience across the broader NLP stack, including embeddings, semantic search, and retrieval-augmented generation (RAG), is highly valued.
- How does Docusign support employees with disabilities during the application process for the Machine Learning Engineering Manager role?
- Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities. If you need assistance during the application process, please contact accommodations@docusign.com.
- What kind of impact can a Machine Learning Engineering Manager have at Docusign?
- As a Machine Learning Engineering Manager, you will lead the development of industry-leading AI/ML solutions that enhance customer experiences and automate processes within the Docusign Agreement Platform, directly impacting business-critical data and efficiency.