Senior Machine Learning Engineer
Role details
Job location
Tech stack
Job description
We are looking for a Senior Machine Learning Engineer to redefine how we operate our global services. You won't 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 the Sr. 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 models-from 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
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.
Requirements
- 8+ years of professional experience in Machine Learning Engineering or Data Science
- Experience with PyTorch or TensorFlow, specifically regarding Time Series analysis (forecasting/anomaly detection) and NLP
- Experience building applications using LLMs (RAG pipelines, LangChain, vector databases) specifically for technical domains (code analysis, log parsing)
- Experience with 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)
- Expereience with 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
Benefits & conditions
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: $177,900.00 - $287,425.00 base salary
Washington, Maryland, New Jersey and New York (including NYC metro area): $170,900.00 - $251,325.00 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
- 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.
