Senior Machine Learning Engineer

UNAVAILABLE; Seattle (WA); Hybrid; USD 178,900 - 262,825; Full time

Benefits offered by this job

Paid Time Off

Paid Parental Leave

Full Health Benefits Plans

Retirement Plans

Learning and Development options

Job summary

Docusign is seeking a Senior Machine Learning Engineer to enhance our global services through advanced AI architectures. This hybrid position requires expertise in Machine Learning and Data Science to design AI solutions that manage complex datasets effectively.

Responsibilities include developing multi-agent systems, deploying deep learning models, and collaborating with Applied Scientists. Candidates should have a solid foundation in technologies like PyTorch, TensorFlow, and Kubernetes.

The role offers competitive compensation and extensive benefits including health plans and paid parental leave.

Qualifications

• 8+ years of professional experience in Machine Learning Engineering or Data Science.
• Experience with PyTorch or TensorFlow.
• Experience building applications using LLMs.

Responsibilities

• Design and implement autonomous multi-agent systems using RL.
• Develop deep learning models for anomaly detection.
• Optimize pipelines for low latency on streaming data.

Skills

Machine Learning Engineering

Data Science

PyTorch

TensorFlow

Reinforcement Learning

NLP

Apache Kafka

Python

C++

Go

Education

8+ years of experience in Machine Learning or Data Science

Tools

Kubernetes

TensorFlow

OpenTelemetry

Grafana

Prometheus

Job description

What you’ll do

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.

Responsibilities

• 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.

What you bring

Basic

• 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)
• Experience 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

Wage Transparency

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.

• California: $186,100.00 - $300,550.00 base salary
• Washington, Maryland, New Jersey and New York (including NYC metro area): $178,900.00 - $262,825.00 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).

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

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 [e-mail].

States Not Eligible for Employment

This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming.

EEO Statement

It’s important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category.