Senior Machine Learning Engineer

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 peoples 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 Docusigns 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 looking for a Senior Machine Learning Engineer to redefine how we operate our global services. You wont just be building dashboards; you will be building the brain of our infrastructure. We are moving beyond simple anomaly detection. We are building a self-healing ecosystem where Multi-Agent Systems and Reinforcement Learning (RL) loops work in tandem with Large Language Models (LLMs) to not only detect incidents in real-time but to troubleshoot and resolve them autonomously. If you are passionate about applying complex AI architectures to massive datasets (billions of telemetry points) to solve real-world reliability challenges this is the role for you.

This position is an individual contributor role reporting to Senior Director Software Engineering.

Responsibility

• Design and implement autonomous multi-agent systems using Reinforcement Learning (RL) loops that can interact with our infrastructure to perform safe automated remediation actions

• Build GenAI agents capable of digesting logs traces and metrics to provide Human-in-the-loop root cause analysis and conversational debugging for our SREs

• Develop and deploy deep learning models (Transformers LSTMs etc.) for forecasting and anomaly detection on high-cardinality high-volume time series data

• Optimize inference pipelines to run with low latency on streaming telemetry data (Kafka/Flink) ensuring we catch issues the moment they happen

• Own the lifecycle of your modelsfrom feature engineering on petabyte-scale datasets to training deployment and monitoring in production Kubernetes environments

• Collaborate with Applied Scientists to translate bleeding-edge research (e.g. causal inference decision transformers) into production-hardened AIOps tools

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 positions job designation depending on business needs and as permitted by local law.

Basic

• 5 years of professional experience in Machine Learning Engineering or Data Science with a strong background in Software Engineering

• Deep understanding of PyTorch or TensorFlow specifically regarding Time Series analysis (forecasting/anomaly detection) and NLP

• Proven experience building applications using LLMs (RAG pipelines LangChain vector databases) specifically for technical domains (code analysis log parsing)

• Practical knowledge of RL concepts (policies rewards agents) and experience applying them to optimization or control problems

• Experience with distributed data processing and streaming technologies (Apache Spark Kafka Flink)

• Strong software engineering fundamentals (Python C or Go) CI/CD for ML and experience deploying models via APIs (FastAPI Triton Inference Server)
  

Preferred

• Familiarity with the three pillars (Logs Metrics Traces) and tools like Prometheus Grafana OpenTelemetry or Jaeger

• Experience with frameworks like AutoGen CrewAI or Ray RLlib

• Deep experience with AWS/GCP/Azure and Kubernetes (K8s) orchestration

• A background in control theory or causal inference

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 whats 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 youll 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 .

If you experience any issues concerns or technical difficulties during the application process please get in touch with our Talent organization at for assistance.

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