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Machine Learning Engineer
- San Francisco, California, United States
- San Francisco, California, United States
Über
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 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
States Not Eligible for Employment This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming.
Equal Opportunity Employer It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can‑do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category.
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Sprachkenntnisse
- English
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