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Distributed Systems Engineer Jobs in Seattle, WA

General Robotics

Systems Engineer

Redmond, WA · On-site

$155K - $205K/yr

Architect and manage distributed systems for efficient resource utilization across heterogeneous ... Strong systems programming skills in one or more of: C++, Rust, Go, Python. * Solid understanding ...

General Robotics

Systems Engineer

Redmond, WA · On-site

C++, Rust, Go, Python. • Solid understanding of operating systems, networking, and distributed ... programming and CUDA optimization for ML workloads. • Experience designing and scaling ...

Nscale

Systems Engineer

Seattle, WA · On-site

Validate node-to-node system performance across distributed environments * Troubleshoot hardware ... engineering, hardware deployment, or data center operations * Hands-on experience deploying server ...

Nscale

Systems Engineer

Seattle, WA

Validate node-to-node system performance across distributed environments * Troubleshoot hardware ... engineering, hardware deployment, or data center operations * Hands-on experience deploying server ...

Meta

Software Systems Engineer

Bellevue, WA

$144K/yr

Meta is seeking a Software Systems Engineer to join our Production Systems Engineering organization ... Experience designing and operating distributed systems software at scale, including monitoring ...

Nscale

Senior Systems Engineer

Seattle, WA

$118K - $162K/yr

Lead the design and development of large-scale distributed systems (1000+ nodes) * Own critical ... Mentor and guide engineers, raising the technical bar across the team * Diagnose and resolve ...

Nscale

Systems Engineer - Early Career

Seattle, WA

As a System Engineer, you will work alongside experienced Systems, Network, and Platform Engineers ... distributed systems while developing practical software solutions that support real-world ...

Nscale

Systems Engineer - Early Career

Seattle, WA · On-site

$80K - $130K/yr

As a System Engineer, you will work alongside experienced Systems, Network, and Platform Engineers ... Interest in distributed systems, networking, infrastructure, or AI/HPC environments Technologies ...

SpaceX

Power Systems Engineer (Starlink)

Redmond, WA · On-site

$115K - $140K/yr

Data/phone distribution and wiring. * Building and site grounding systems * Fire alarm systems and lightning protection systems * Provide electrical engineering support to facility technicians to ...

SpaceX

Power Systems Engineer (Starlink)

Redmond, WA · On-site

$115K - $140K/yr

Electrical power distribution systems * Switch-gear and motor control centers * Exterior and ... Provide engineering support for the design, operation, and troubleshooting of all the facility ...

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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

$144.9K

$190.2K

How much do distributed systems engineer jobs pay per year?

As of Jul 20, 2026, the average yearly pay for distributed systems engineer in Seattle, WA is $144,855.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,600.00 and $178,800.00 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 89% Full Time, 7% Part Time, 1% Temporary, and 3% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $144,855 per year, or $69.6 per hour.

Staff ML Systems Engineer, Distributed Systems

FieldAI

Seattle, WA

$195K - $230K/yr

Full-time

Re-posted 21 days ago

Job description

FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.

We are seeking a Staff ML Systems Engineer to architect and build the distributed infrastructure that powers large-scale machine learning workflows across the organization.

This role sits at the intersection of machine learning, distributed systems, and platform engineering. You will be responsible for designing scalable systems that support data processing, model training, evaluation, and post-processing pipelines while enabling ML teams to efficiently develop, operate, and scale production-grade workflows.

You will play a critical role in defining the architectural patterns, tooling, and infrastructure that underpin our machine learning platform.

What You'll Get To Do
  • Design and build scalable distributed machine learning pipelines across data processing, model training, evaluation, and post-processing workflows.
  • Architect distributed execution systems, including parallelization strategies, workload scheduling, resource allocation, and fault tolerance mechanisms.
  • Develop reusable abstractions, frameworks, and libraries that simplify distributed pipeline development.
  • Optimize performance across distributed CPU and GPU environments, improving throughput, utilization, and reliability.
  • Design systems that effectively manage data partitioning, memory utilization, serialization overhead, and compute efficiency.
  • Partner closely with ML engineers, data engineers, and infrastructure teams to productionize research workflows and enable large-scale model development.
  • Establish best practices and engineering standards for distributed machine learning infrastructure.
  • Evaluate and guide decisions around distributed computing frameworks, infrastructure technologies, and system design trade-offs.
  • Improve observability, debugging, monitoring, and operational tooling for distributed systems at scale.
What You Have
  • 5+ years of experience building distributed systems, backend infrastructure, machine learning platforms, or large-scale data processing systems.
  • Strong Python programming skills, including experience with concurrency, performance optimization, and systems development.
  • Experience with distributed computing frameworks such as Ray, Spark, Dask, Flink, or similar technologies.
  • Experience designing and scaling data pipelines or machine learning workflows.
  • Strong system design skills with demonstrated expertise in scalability, reliability, and performance optimization.
  • Experience diagnosing and resolving bottlenecks in distributed environments.
  • Ability to work cross-functionally and drive technical decisions across multiple teams.
The Extras That Set You Apart
  • Experience building infrastructure for machine learning training and inference systems.
  • Familiarity with modern ML frameworks such as PyTorch or TensorFlow.
  • Experience with multi-node or multi-GPU training architectures, including DDP, FSDP, DeepSpeed, or similar technologies.
  • Experience operating Kubernetes-based infrastructure and large-scale cloud systems.
  • Deep understanding of distributed systems concepts including data locality, serialization costs, scheduling, and resource management.
  • Experience with distributed debugging, observability, and workflow orchestration platforms.
  • Proven ability to establish technical direction and influence architecture across organizations.

Our salary range is highly competitive with the market, but we take into consideration an individual's background and experience in determining final salary. Base pay offered may vary depending on geographic location, job-related knowledge, skills, and experience.

In addition to competitive compensation, FieldAI offers comprehensive benefits, equity participation, and the opportunity to contribute to cutting-edge advancements in AI and robotics.

Our salary range is generous and we consider each individual’s background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.

Why Join FieldAI in Irvine?
In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics’ hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.
You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.

Be Part of the Next Robotics Revolution
We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.

Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like.

We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected statu

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.