Machine Learning Engineer

$122,300 - $190,650/Yr

DocuSign - San Francisco, CA

Full-time - Mid Level

Remote - San Francisco, CA

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

Docusign is seeking a passionate and collaborative Machine Learning Engineer to join the AI Infrastructure team. This role focuses on building a centralized platform for creating, managing, and deploying advanced AI/ML solutions to enhance customer journeys within Docusign's Intelligent Agreement Management. The engineer will support the entire machine learning lifecycle, collaborating with applied researchers to prototype and productionize solutions for real business use cases at scale.

Responsibilities

• Collaborate with Applied Science, Product, and other engineers across multiple offices and time zones to create and deliver new machine learning products and features on time.
• Contribute to the development of AI infrastructure by building highly scalable gRPC-based services to enable offline and online machine learning pipelines, ensuring enterprise-grade security and reliability.
• Develop systems to optimize and create AI-assisted data labeling processes while maintaining appropriate and thorough data governance and security standards.
• Contribute to the development of scalable model training infrastructure to minimize the time it takes to deploy the candidate models to production.
• Optimize model performance, including open source and licensed LLMs, in production, using best practices for CPU/GPU inference on NVIDIA Triton with TensorRT/ONNX.
• Improve platform observability by implementing tools and required infrastructure to monitor and analyze the performance of deployed AI services.

Requirements

• 2+ years of related experience with a Bachelor's degree; or a Master's degree without experience; or equivalent in experience.
• Experience building and consuming RESTful and gRPC based web-services.
• Experience with CI/CD build pipelines, integrated tests, and test-driven development.
• Experience with cloud deployment technologies, such as Kubernetes or Docker containers.
• Experience with designing and scaling fullstack or distributed backend systems using the microservice architecture.
• Experience and advanced proficiency with Java, Python or similar programming languages.

Nice-to-haves

• Experience building machine learning products, data pipelines, or machine learning training and deployment systems.
• Experience with deployment and monitoring of machine learning models.
• Ability and desire to move across technology stacks fluently and easily.
• Experience with LLMs.
• Familiarity with NLP, Computer Vision domains.
• Familiarity with Open AI APIs and libraries.

Benefits

• 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.