Machine Learning Engineer

Docusign • Seattle, WA

12h • Hybrid

About The Position

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

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).
• 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