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Selected role

Machine Learning Engineer

DocuSign San Francisco, CA, US

$158k - $266k Senior Full-time

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

As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign’s next generation of intelligent systems. You will bridge the gap between core AI research and production-grade engineering, developing scalable platforms for autonomous agents, advanced retrieval systems, and automated model optimization.

This position is an individual contributor role reporting to the

Director, Machine Learning Engineering

Responsibility

Build and maintain high-performance distributed systems to support large-scale model inference and data processing
Design frameworks for multi-agent systems, focusing on state management, reliability, and long-running autonomous workflows
Architect sophisticated Retrieval-Augmented Generation (RAG) pipelines and advanced context management strategies to improve model accuracy and relevance
Develop platform-level tools for automated prompt engineering, evaluation, and optimization to accelerate the AI development lifecycle
Implement robust ML pipelines, focusing on observability, versioning, and the seamless deployment of generative AI services

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 machine learning engineering, software engineering, or related operational roles
Experience in software engineering with a focus on distributed systems and scalable backend architecture
Deep understanding of the ML lifecycle, from data ingestion and training to production monitoring
Experience building with LLMs, including RAG architectures and sophisticated prompt engineering
Experience deploying and maintaining ML models in high-traffic, production environments
Expertise in Python and experience with modern ML frameworks such as PyTorch

Preferred

Experience with distributed task queues or stateful workflow engines for managing complex, multi-step AI processes
Experience with frameworks designed for horizontal scaling of compute-intensive ML workloads
Experience designing "agent-loop" architectures that involve tool-use, self-correction, and multi-step reasoning
Familiarity with vector storage systems and high-throughput data processing pipelines

Wage Transparency

Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.

Based on applicable legislation, the below details pay ranges in the following locations:

California: $164,700.00 - $266,000.00 base salary

Washington: $158,300.00 - $232,575.00 base salary

This role is also eligible for the following:

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

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.

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