Machine Learning Engineer

Docusign • Seattle, WA

1d • Hybrid

About The Position

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).

Docusign is looking for a passionate, talented, and collaborative Machine Learning Engineer to join our AI Infrastructure team. Our team is responsible for building Docusign’s centralized platform to create, manage and deploy advanced AI/ML solutions to make customer journeys throughout the Docusign Agreement Cloud more efficient. As a Machine Learning engineer, you will help support all aspects of the machine learning lifecycle, including the research platform, training and deployment pipelines, labeling and serving infrastructure. You will partner with a team of expert applied researchers who specialize in various domains, including document understanding, natural language processing (NLP), computer vision, and more to prototype and productionize solutions for real business use-cases at scale.

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

Requirements

• Bachelor’s degree in Computer Science, or a related technical field (or equivalent experience)
• Experience with internships or applicable academic projects
• Experience with at least one major programming language, preferably Python or C#
• Experience with data structures, algorithms, and software engineering fundamentals
• Experience with version control systems (e.g., git) and writing unit tests
• Experience with RESTful APIs and how web services work
• Applicants must already be authorized to work in the United States on a full-time, permanent basis without the need for current or future sponsorship.

Nice To Haves

• Previous internship experience in software engineering, data engineering, or machine learning
• Coursework or academic projects related to Machine Learning, Natural Language Processing (NLP), or Computer Vision
• Familiarity with containerization technologies like Docker or Kubernetes
• Exposure to cloud platforms (AWS, Azure, or GCP)
• Interest in Large Language Models (LLMs) and Generative AI
• Experience with SQL or data processing libraries (e.g., Pandas, NumPy)

Responsibilities

• Write clean, maintainable, and well-tested code for AI infrastructure services and data pipelines under the guidance of senior engineers
• Assist in building and maintaining CI/CD pipelines and workflows that automate model training and deployment
• Help monitor the performance of deployed AI services by implementing logging, metrics, and alerting (observability) to ensure system reliability
• Partner with Applied Scientists and Product Managers to understand requirements and help operationalize ML models for document understanding and NLP tasks
• Author unit and integration tests for your code components to ensure high quality and stability of the AI platform
• Develop scripts and small tools to support data labeling processes and ensure data governance standards are met
• Learn about new ML technologies (LLMs, Triton Inference Server, Kubernetes) and engineering best practices through code reviews and mentorship actively

Benefits

• Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
• Stock: This role is eligible to receive Restricted Stock Units (RSUs).
• Global benefits provide options for the following:
• Paid Time Off: earned time off, as well as paid company holidays based on region
• Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
• Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
• Retirement Plans: select retirement and pension programs with potential for employer contributions
• Learning and Development: options for coaching, online courses and education reimbursements
• Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level