Senior Machine Learning Engineer

DocuSign DocuSign · Enterprise · Bangalore, India · Engineering

Senior Machine Learning Engineer at DocuSign, focusing on the architecture and delivery of a Packaging and Application Lifecycle Management (ALM) platform. This role involves building scalable, extensible, and reliable platform capabilities for product teams, partners, and ISVs. The engineer will own end-to-end solution design, lead cross-team initiatives, and influence technical direction, working with Product, Architecture, and Engineering teams in a globally distributed environment. The position is an individual contributor role.

What you'd actually do

  1. Lead the architecture and delivery of the Packaging and ALM platform, driving technical vision and execution for a strategic initiative
  2. Design scalable, fault-tolerant, and extensible platform services using modern microservices and cloud-native architectures
  3. Own end-to-end technical design for complex, cross-system workflows and integrations
  4. Author and present high-quality engineering design documents and drive alignment with senior stakeholders
  5. Act as the technical DRI for large cross-team programs, ensuring clarity of scope, dependencies, timelines, and risks

Skills

Required

  • 12+ years of professional experience in software engineering
  • Proven experience leading the design and delivery of large-scale, distributed systems and platform initiatives
  • Strong expertise in system design, microservices architecture, and cloud-native application development
  • Hands-on experience building scalable backend services using modern programming languages such as Node.js, C#, Java, or Go
  • Experience with containerization and orchestration platforms such as Kubernetes
  • Strong understanding of multi-region architectures, high availability, resiliency, and disaster recovery
  • Experience designing and evolving platform APIs, service contracts, and extensible frameworks
  • Bachelor’s or Master’s degree in Computer Science or a related field

Nice to have

  • Experience building packaging, deployment, ALM, or platform engineering solutions.
  • Familiarity with DevOps practices, CI/CD pipelines, release orchestration, and environment promotion workflows.
  • Experience with dependency management, versioning strategies, and artifact lifecycle management.
  • Exposure to REST and GraphQL API design and event-driven architectures.
  • Experience with observability and operational excellence tools such as Prometheus, Grafana, or Datadog.
  • Understanding of authentication and authorization standards such as OAuth2, OpenID Connect, and JWT.
  • Experience working on SaaS platforms serving external developers, partners, or ISVs.
  • Excellent communication and collaboration skills with experience working across globally distributed teams
  • Proven ability to mentor senior engineers and lead through influence
  • Demonstrated ability to create high-quality design documentation and present technical solutions to diverse stakeholders

What the JD emphasized

  • large-scale, distributed systems
  • microservices architecture
  • cloud-native application development
  • scalable backend services
  • Kubernetes
  • multi-region architectures
  • high availability
  • resiliency
  • disaster recovery
  • platform APIs
  • service contracts
  • extensible frameworks
  • packaging, deployment, ALM, or platform engineering solutions
  • DevOps practices
  • CI/CD pipelines
  • release orchestration
  • environment promotion workflows
  • dependency management
  • versioning strategies
  • artifact lifecycle management
  • event-driven architectures
  • observability
  • operational excellence tools
  • SaaS platforms serving external developers, partners, or ISVs