What you'd actually do

Drive the architectural vision and implementation of event-driven, distributed systems that support large-scale data procurement, annotation, and storage for the IAM platform

Set the standard for high-quality, shippable code; perform rigorous code reviews and mentor junior engineers to ensure the team's output is maintainable, scalable, and tested

Act as the primary technical point of contact for Applied Science and Product teams, translating high-level business requirements into successful, timely deliveries of ML products

Oversee the development of production-grade data pipelines that facilitate analytics, evaluation, and model development, and at scale

Lead the creation of vital infrastructure and services to optimize the performance of complex, multi-layered machine learning systems

What the JD emphasized

12+ years of related experience with a Bachelor’s degree; or 8 years related experience with a Master’s degree; or equivalent experience

Proven ability to lead engineering projects from ideation to production with minimal supervision while empowering junior team members

Expertise in CI/CD build pipelines, integration testing, and test-driven development (TDD) for large-scale deployments

Expertise in cloud deployment technologies, specifically Kubernetes (k8s) and Docker containers, to manage distributed AI services

Advanced experience building specialized ML features, including vector storage systems, complex data pipelines, and intelligent storage solutions

Other signals

builds Machine Learning solutions

power insights and automation

simplify and optimize business processes

automated expertise

support all aspects of the machine learning lifecycle

data, annotation, training and evaluation systems

distributed, scalable systems

builds analytics products using cutting-edge deep learning based models

Drive the architectural vision and implementation of event-driven, distributed systems

support large-scale data procurement, annotation, and storage

production-grade data pipelines

optimize the performance of complex, multi-layered machine learning systems

building scalable, reliable, and high-performance software architectures for AI-driven products

building specialized ML features

vector storage systems

complex data pipelines

intelligent storage solutions

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 The Docusign AI team builds Machine Learning solutions that power insights and automation for Docusign Intelligent Agreement Management (IAM). Our ultimate goal is to simplify and optimize business processes around contract negotiation, execution, and post-signature analysis by empowering customers with automated expertise. We are looking for passionate and talented Machine Learning Engineers to build AI Applications and user experiences that will power Docusign’s IAM. In this role, you will help support all aspects of the machine learning lifecycle, specifically areas like data, annotation, training and evaluation systems, and distributed, scalable systems. This role will be a part of the AI Applications team, which builds analytics products using cutting-edge deep learning based models and works collaboratively across our distributed teams. This position is an individual contributor role reporting to the Senior Engineering Manager. Responsibility Drive the architectural vision and implementation of event-driven, distributed systems that support large-scale data procurement, annotation, and storage for the IAM platform Set the standard for high-quality, shippable code; perform rigorous code reviews and mentor junior engineers to ensure the team's output is maintainable, scalable, and tested Act as the primary technical point of contact for Applied Science and Product teams, translating high-level business requirements into successful, timely deliveries of ML products Oversee the development of production-grade data pipelines that facilitate analytics, evaluation, and model development, and at scale Lead the creation of vital infrastructure and services to optimize the performance of complex, multi-layered machine learning systems 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 related experience with a Master’s degree; or equivalent experience Proven ability to lead engineering projects from ideation to production with minimal supervision while empowering junior team members Proven track record building and consuming production-grade RESTful and gRPC-based web services Expertise in CI/CD build pipelines, integration testing, and test-driven development (TDD) for large-scale deployments Expertise in cloud deployment technologies, specifically Kubernetes (k8s) and Docker containers, to manage distributed AI services Professional experience with batch processing and workflow management tools Preferred Demonstrated success in building scalable, reliable, and high-performance software architectures for AI-driven products Advanced experience building specialized ML features, including vector storage systems, complex data pipelines, and intelligent storage solutions Ability to move across technology stacks with ease and provide technical guidance on distributed service architectures to junior engineers Expert-level proficiency in writing and architecting applications primarily in Java and Python 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-VP3

Lead Machine Learning Engineer

What you'd actually do

Skills

Required

Nice to have

What the JD emphasized

Other signals