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Distributed Systems Engineer Jobs in Seattle, WA

Ziply Fiber

Senior Systems Engineer

Kirkland, WA · Remote

$99K - $151K/yr

Senior Systems Engineer Base Salary: $99,200 to $151,300 annually DOE Benefits: Medical, dental ... Minimum of seven (7) years working in a large, geographically distributed server architecture.

City of Tacoma

Power Systems Engineer

Tacoma, WA · On-site

$98K - $184K/yr

Position Description Tacoma Power's Transmission & Distribution (T&D) Section is seeking a Power System Engineer (Power Systems Engineer, Associate, Power Systems Engineer, or Power Systems Engineer ...

Ziply Fiber

Systems Engineer II

Everett, WA

$90K - $137K/yr

Systems Engineer II Base Salary: $90,200 to $137,500 annually DOE Benefits: Medical, dental, vision ... distributed server architecture. · Minimum of five (5) years of experience working with ...

Vale Concepts

Embedded Systems Engineer

Seattle, WA

$118K - $155K/yr

We're looking for an embedded robotics engineer to help design and build the distributed embedded system that powers these machines. You'll work across firmware, real-time control, device ...

Vale Concepts

Embedded Systems Engineer

Seattle, WA · On-site

$118K - $155K/yr

We're looking for an embedded robotics engineer to help design and build the distributed embedded system that powers these machines. You'll work across firmware, real-time control, device ...

Helion Energy

Electrical Systems Engineer

Everett, WA · On-site

$165K - $200K/yr

As an Electrical Systems Engineer, you will help define the electrical hardware that powers and ... distribution, controls interfaces, sensors, and communication networks, function together as a ...

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All JobsDistributed Systems Engineer JobsDistributed Systems Engineer Jobs in Seattle, WA

Distributed Systems Engineer information

See Seattle, WA salary details

$60.9K

$144.8K

$190.1K

How much do distributed systems engineer jobs pay per year?

As of Jul 24, 2026, the average yearly pay for distributed systems engineer in Seattle, WA is $144,774.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $178,700.00 per year, depending on experience, location, and employer.

What are the typical daily responsibilities of a Distributed Systems Engineer?

A Distributed Systems Engineer typically spends their days designing, implementing, and testing scalable systems that handle large volumes of data and user requests. You'll collaborate closely with software developers, DevOps engineers, and product managers to architect solutions that ensure reliability, performance, and fault-tolerance. Regular tasks may include reviewing system performance metrics, debugging distributed applications, writing detailed documentation, and participating in code reviews. Engaging in team meetings and cross-functional discussions is also common, as seamless cooperation is vital in this complex and fast-evolving field.

What engineers make $300,000 a year?

Senior distributed systems engineers, software engineers with expertise in scalable architectures, and those working in high-demand industries such as cloud computing or finance can earn $300,000 or more annually. Achieving this level typically requires extensive experience, advanced skills in distributed computing, and often working in senior or specialized roles at large technology companies.

What engineers make 200,000 a year?

Distributed Systems Engineers can earn $200,000 or more annually, especially with extensive experience, advanced skills in cloud computing, distributed architecture, and proficiency in programming languages like Java or Go. Salaries vary based on location, company size, and expertise, with senior roles often reaching or exceeding this level.

What are the key skills and qualifications needed to thrive in the Distributed Systems Engineer position, and why are they important?

To thrive as a Distributed Systems Engineer, you need a strong background in computer science, experience with large-scale system design, and proficiency in languages such as Java, Go, or Python. Familiarity with cloud platforms (like AWS, GCP, or Azure), container orchestration tools (such as Kubernetes), and distributed databases is commonly required, and certifications in cloud computing can be advantageous. Strong problem-solving abilities, collaboration, and excellent communication skills help you navigate complex issues and work effectively across technical teams. These skills are fundamental for designing, implementing, and maintaining robust distributed systems that perform reliably at scale.

What does a distributed systems engineer do?

A distributed systems engineer designs, develops, and maintains systems that run across multiple computers or servers to ensure scalability, reliability, and performance. They work with technologies such as cloud platforms, networking, and programming languages like Java or Python, often focusing on fault tolerance and data consistency. Strong problem-solving skills and knowledge of system architecture are essential for this role.

What engineers make $500,000?

Senior engineers in high-demand fields such as software engineering, especially those specializing in distributed systems, cloud infrastructure, or machine learning, can earn $500,000 or more annually. Achieving this level typically requires extensive experience, advanced skills, and often includes bonuses, stock options, or other compensation components.

What does a Distributed Systems Engineer do?

A Distributed Systems Engineer designs, builds, and maintains large-scale systems that run across multiple machines or data centers. They ensure reliability, scalability, and fault tolerance by using technologies like cloud computing, containerization, and distributed databases. Their work often involves solving complex problems related to data consistency, network latency, and system coordination.

What are the most commonly searched types of Distributed Systems Engineer jobs in Seattle, WA? The most popular types of Distributed Systems Engineer jobs in Seattle, WA are:
What are popular job titles related to Distributed Systems Engineer jobs in Seattle, WA? For Distributed Systems Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Distributed Systems Engineer jobs in Seattle, WA look for? The top searched job categories for Distributed Systems Engineer jobs in Seattle, WA are:
Distributed Systems Engineer jobs near you
Infographic showing various Distributed Systems Engineer job openings in Seattle, WA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 68% In-person, and 32% Remote job distribution, with an average salary of $144,774 per year, or $69.6 per hour.
Software Engineer, Systems ML Engineering

Software Engineer, Systems ML Engineering

Meta

Bellevue, WA • On-site, Remote

$183K/yr

Full-time

Posted 18 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

142nd of 217 rated software companies

Job description

Meta is seeking a Staff Software Engineer to join the Systems ML Engineering team, focused on building and scaling the infrastructure and software systems that power large-scale machine learning workloads across Meta's production fleet. In this role, you will architect and own critical components of the ML systems stack, spanning training infrastructure, model serving, distributed computing frameworks, and ML platform tooling. You will work at the intersection of systems engineering and machine learning to drive reliability, performance, and efficiency for some of the world's most demanding AI workloads, including large language models and generative AI systems.
Software Engineer, Systems ML Engineering Responsibilities:
  • Design and implement scalable ML systems infrastructure components, including distributed training frameworks, model serving pipelines, and ML platform tooling used across Meta's production AI workloads
  • Lead technical design and architecture for major initiatives in the ML systems stack, evaluating trade-offs across performance, reliability, and engineering complexity
  • Identify and resolve performance bottlenecks in distributed ML training and inference systems through instrumentation, profiling, and targeted optimization
  • Define and drive service level objectives for ML infrastructure services, building dashboards, alerting, and runbooks to reduce mean time to mitigation during incidents
  • Collaborate with machine learning researchers, product engineers, and infrastructure teams to translate model development requirements into robust, production-grade systems
  • Leverage AI-assisted development workflows to accelerate implementation, code review, and system analysis, applying sound judgment on when to rely on AI tooling versus deep domain expertise
  • Mentor other engineers on ML systems best practices, distributed computing patterns, and engineering craft, including AI-native development workflows
  • Drive adoption of engineering standards across the team, including testing strategies, staged rollout practices using feature flagging and experimentation frameworks, and proactive monitoring
  • Contribute to roadmap definition and stakeholder alignment for multi-quarter ML infrastructure investments, communicating technical options and trade-offs to both engineering and cross-functional audiences
  • Conduct thorough code reviews and establish coding standards that improve maintainability and scalability of the ML systems codebase

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 8+ years of experience in software engineering with a focus on systems software, distributed computing, or ML infrastructure
  • Experience designing and implementing large-scale distributed systems, including components such as training orchestration, model serving, or data pipeline infrastructure
  • Experience with performance analysis and optimization of compute-intensive or distributed workloads, including profiling, benchmarking, and bottleneck identification
  • Experience leading end-to-end delivery of complex technical projects, including cross-team coordination, milestone planning, and risk mitigation
  • Experience with C++, Python, or equivalent systems programming languages applied to production ML or infrastructure systems

Preferred Qualifications:
  • Experience contributing to or maintaining open-source ML systems or distributed computing projects
  • Experience building or operating ML platform services including experiment tracking, model registries, feature stores, or inference serving infrastructure
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience with ML frameworks such as PyTorch, including distributed training paradigms such as data parallelism, model parallelism, or pipeline parallelism
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Experience with GPU computing, CUDA programming, or accelerator-aware systems optimization for large-scale AI workloads

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$183,997/year to $257,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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