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).
We are seeking an experienced Machine Learning Engineer to join our team and drive the design, development, and optimization of large-scale data processing systems. This role requires deep expertise in distributed computing, data pipeline architecture, modern big data technologies, and applied Large Language Model (LLM) integration.
This position is an individual contributor role reporting to the Machine Learning Engineering Manager.
Responsibility
Architect and maintain high-performance, fault-tolerant distributed systems to ensure scalability and availability
Design, build, and optimize scalable data pipelines and ETL processes using Python, Spark, and Ray to process complex, unstructured datasets
Develop batch data processing workflows to support analytics and machine learning initiatives
Integrate and operationalize Large Language Models (LLMs) such as OpenAl, Azure OpenAl, or similar platforms into production applications, including PII detection and redaction workflows
Design and maintain prompt engineering strategies, fine-tuning pipelines, and evaluation frameworks for LLM-based solutions
Optimize data processing jobs and system performance for cost-efficiency and reliability
Collaborate with applied scientists, SMEs, and engineering teams to understand data requirements and deliver robust solutions
Implement data quality frameworks and monitoring systems to ensure data integrity
Troubleshoot and resolve complex data processing issues in production environments
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.
Basic
5+ years of experience in data engineering or related roles
Experience with Python for data engineering and automation
Experience with distributed computing frameworks like Apache Spark or Ray
Experience integrating LLMs (e.g., OpenAl, Azure OpenAl, Anthropic, or similar) into applications via APIs, including prompt design, response parsing, and error handling
Experience with distributed systems concepts including data partitioning and sharding strategies, fault tolerance and replication, consistency models and distributed consensus, load balancing and resource management
Experience with distributed file systems (Azure Data Lake, S3, HDFS)
Experience implementing REST APIs using Python frameworks such as FastAPI, Flask, or similar
Experience with containerization and orchestration (Docker, Kubernetes)
Experience with SQL and database optimization techniques
Experience with data structures, algorithms, and software design patterns
Experience with version control systems (Git) and CI/CD pipelines
Bachelor's or Master's degree in Computer Science, Engineering, or related field, or equivalent practical experience
Preferred
Experience working with unstructured data (text, images, video, audio) and associated processing techniques
Experience with multiple cloud platforms (e.g., AWS, Azure, GCP)
Knowledge of data governance and security best practices
Experience with machine learning pipelines and MLOps
Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex)
Familiarity with responsible Al practices, including bias mitigation, content filtering, and token cost optimization for LLM-based applications
Contributions to open-source projects
Excellent problem-solving skills and ability to work with complex, ambiguous requirements
Strong communication skills and ability to collaborate across teams
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.
