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Remote Reinforcement Learning Jobs in Seattle, WA

Senior Machine Learning Engineer

Seattle, WA · On-site +1

$186K - $300K/yr

  • Medical

  • Life

  • Retirement

  • PTO

We are building a self-healing ecosystem where Multi-Agent Systems and Reinforcement Learning (RL ... Employee divides their time between in-office and remote work. Access to an office location is ...

We use reinforcement learning algorithms to provide this intelligence, converting raw sensor data ... We are a 100% remote company. * Competitive compensation & meaningful equity. * Outsized ...

Expression of Interest - Engineering

Seattle, WA · Remote

$19 - $24.75/hr

We use reinforcement learning algorithms to provide this intelligence, converting raw sensor data ... We are a 100% remote company. * Competitive compensation & meaningful equity. * Outsized ...

... remote Who We Need We are seeking a highly motivated and talented Machine Learning PhD Intern to ... Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback ...

Remote Reinforcement Learning information

See Seattle, WA salary details

$12.5K

$95.5K

$159.3K

How much do remote reinforcement learning jobs pay per year?

As of Aug 14, 2026, the average yearly pay for remote reinforcement learning in Seattle, WA is $95,464.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,900.00 and $158,200.00 per year, depending on experience, location, and employer.

What is a remote reinforcement learning?

A Remote Reinforcement Learning job involves developing and applying reinforcement learning algorithms while working from a location outside of a traditional office environment. Professionals in this field focus on creating systems where agents learn optimal behaviors through trial and error, often using feedback from their environment. These jobs typically require expertise in machine learning, programming, and mathematics, and are commonly found in industries like robotics, gaming, and autonomous systems. Working remotely allows researchers and engineers to collaborate with global teams using digital tools and platforms.

What are the key skills and qualifications needed to thrive as a remote reinforcement learning engineer?

To thrive as a Remote Reinforcement Learning Engineer, you need a strong background in machine learning, statistics, and programming (especially Python), often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and RL-specific libraries like OpenAI Gym, along with experience using cloud computing platforms, is typically required. Excellent problem-solving skills, self-motivation, and effective remote communication help individuals excel in distributed teams. These skills ensure the successful design, implementation, and deployment of reinforcement learning solutions while collaborating efficiently in a remote work environment.

What is the difference between Remote Reinforcement Learning vs Remote Machine Learning Engineer?

AspectRemote Reinforcement Learning
Required CredentialsMaster's or PhD in Computer Science, AI, or related fields; knowledge of RL algorithms
Work EnvironmentResearch-focused, experimental, often involves simulation and algorithm development
Employer & Industry UsageTech companies, research labs, AI startups focusing on autonomous systems
Common Search & Comparison IntentUnderstanding specialized AI roles, research focus, and technical skills

Remote Reinforcement Learning specialists focus on developing algorithms that enable machines to learn through trial and error in simulated or real environments. In contrast, Remote Machine Learning Engineers typically work on deploying and optimizing various machine learning models across applications. While both roles require strong programming skills and knowledge of AI, reinforcement learning emphasizes decision-making processes, whereas machine learning engineering covers a broader range of models and deployment strategies.

What are common challenges faced when working remotely in a reinforcement learning role and how can they be addressed?

Working remotely in a Reinforcement Learning role often involves overcoming communication barriers with cross-functional teams, managing large-scale experiments without on-site resources, and staying updated with rapidly evolving research. To address these challenges, it's important to establish regular check-ins with colleagues, utilize cloud-based platforms for experiment management, and participate in virtual seminars or journal clubs. Developing strong self-motivation and time management skills is also crucial to maintain productivity in a remote environment.

What are the most commonly searched types of Reinforcement Learning jobs in Seattle, WA?

The most popular types of Reinforcement Learning jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Remote Reinforcement Learning jobs?

Cities near Seattle, WA with the most Remote Reinforcement Learning job openings:

Infographic showing various Remote Reinforcement Learning job openings in Seattle, WA as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% Remote job distribution, with an average salary of $95,464 per year, or $45.9 per hour.

Senior Machine Learning Engineer

DocuSign

Seattle, WA • On-site, Remote

$186K - $300K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 16 days ago


DocuSign rating

9.9

Company rating: 9.9 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

1st of 244 rated software companies


Job description

Company Overview

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 people's 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 Docusign's 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).

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.

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.

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)

  • 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

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.

Based on applicable legislation, the below details pay ranges in the following locations:

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).

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
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.

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 accommodations@docusign.com.

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

Applicant and Candidate Privacy Notice

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.

EEO Know Your Rights poster

Employment Type: FULL_TIME

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