They are seeking a Senior / Staff ML Systems Engineer to architect and build distributed infrastructure for large-scale machine learning workflows, enabling efficient development and operation of ...
They are seeking a Senior / Staff ML Systems Engineer to architect and build distributed infrastructure for large-scale machine learning workflows, enabling efficient development and operation of ...
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 ...
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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 ...
Senior Distributed Systems Engineer - Kotlin/Spring
Seattle, WA · On-site
$138K - $226K/yr
Senior Distributed Systems Engineer - Kotlin/Spring Senior Distributed Systems Engineer - Kotlin/Spring Location: This role enables associates to work virtually full-time, except for required in ...
Senior Distributed Systems Engineer - Kotlin/Spring
Seattle, WA · On-site
$138K - $226K/yr
Senior Distributed Systems Engineer - Kotlin/Spring Senior Distributed Systems Engineer - Kotlin/Spring Location: This role enables associates to work virtually full-time, except for required in ...
Staff ML Systems Engineer, Distributed Systems
$195K - $230K/yr
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 ...
Staff ML Systems Engineer, Distributed Systems
$195K - $230K/yr
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 ...
Distributed Systems Engineer, Instructional Products
Seattle, WA · On-site
$139K - $258K/yr
Description We are seeking a Distributed Systems Engineer with expertise in building Restful APIs, Search and a working knowledge of machine learning concepts and systems. Your role will primarily ...
Distributed Systems Engineer, Instructional Products
Seattle, WA · On-site
$139K - $258K/yr
Description We are seeking a Distributed Systems Engineer with expertise in building Restful APIs, Search and a working knowledge of machine learning concepts and systems. Your role will primarily ...
Senior Distributed Systems Engineer - Kotlin/Spring
Seattle, WA · On-site
$138K - $226K/yr
Senior Distributed Systems Engineer - Kotlin/Spring Location: This role enables associates to work virtually full-time, except for required in-person training sessions, providing maximum flexibility ...
Senior Distributed Systems Engineer - Kotlin/Spring
Seattle, WA · On-site
$138K - $226K/yr
Senior Distributed Systems Engineer - Kotlin/Spring Location: This role enables associates to work virtually full-time, except for required in-person training sessions, providing maximum flexibility ...
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 ...
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 ...
Distributed Systems Engineer 6 - Decisioning & Optimization
Seattle, WA · On-site
$118K - $162K/yr
... engineering team sits within the Ad Serving & Decisioning at Netflix Ads. We own the systems that ... distributed systems and backend services at large scale; 3+ years in the ads domain * Deep ...
Distributed Systems Engineer 6 - Decisioning & Optimization
Seattle, WA · On-site
$118K - $162K/yr
... engineering team sits within the Ad Serving & Decisioning at Netflix Ads. We own the systems that ... distributed systems and backend services at large scale; 3+ years in the ads domain * Deep ...
We are looking for a strong systems engineer to build and scale the core infrastructure behind ads ... building distributed systems and backend services at scale * Ads domain experience (2+ years ...
We are looking for a strong systems engineer to build and scale the core infrastructure behind ads ... building distributed systems and backend services at scale * Ads domain experience (2+ years ...
We are looking for a strong systems engineer to build and scale the core infrastructure behind ads ... distributed systems and backend services at scale Ads domain experience (2+ years): worked on ad ...
We are looking for a strong systems engineer to build and scale the core infrastructure behind ads ... distributed systems and backend services at scale Ads domain experience (2+ years): worked on ad ...
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 ...
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 ...
... engineering team sits within the Ad Serving & Decisioning at Netflix Ads. We own the systems that ... distributed systems and backend services at large scale; 3+ years in the ads domain Deep experience ...
... engineering team sits within the Ad Serving & Decisioning at Netflix Ads. We own the systems that ... distributed systems and backend services at large scale; 3+ years in the ads domain Deep experience ...
LLM Pre-training & Distributed Engineer (AI Infrastructure)
Seattle, WA · On-site
$122K - $160K/yr
We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing distributed ...
LLM Pre-training & Distributed Engineer (AI Infrastructure)
Seattle, WA · On-site
$122K - $160K/yr
We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing distributed ...
LLM Pre-training & Distributed Engineer (AI Infrastructure)
Seattle, WA · On-site
$122K - $160K/yr
We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing distributed ...
LLM Pre-training & Distributed Engineer (AI Infrastructure)
Seattle, WA · On-site
$122K - $160K/yr
We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing distributed ...
Systems Engineer
Seattle, WA · On-site
... distributed environments • Troubleshoot hardware, firmware, and infrastructure-level issues • Assist with system reliability and performance optimization • Contribute to automation for ...
Systems Engineer
Seattle, WA · On-site
... distributed environments • Troubleshoot hardware, firmware, and infrastructure-level issues • Assist with system reliability and performance optimization • Contribute to automation for ...
Systems Engineer, Prime Air
Seattle, WA · On-site
Geospatial engineering, Weather Science, Distributed Systems, Flight Decks, or Traffic Management. - Experience in cloud based software development, system design, and/or distributed system ...
Systems Engineer, Prime Air
Seattle, WA · On-site
Geospatial engineering, Weather Science, Distributed Systems, Flight Decks, or Traffic Management. - Experience in cloud based software development, system design, and/or distributed system ...
Validate node-to-node system performance across distributed environments * Troubleshoot hardware ... engineering, hardware deployment, or data center operations * Hands-on experience deploying server ...
Validate node-to-node system performance across distributed environments * Troubleshoot hardware ... engineering, hardware deployment, or data center operations * Hands-on experience deploying server ...
Sr. Systems Engineer, Prime Air
Seattle, WA · On-site
$118K - $162K/yr
Geospatial engineering, Weather Science, Distributed Systems, Flight Decks, or Traffic Management. - Experience in cloud based software development, system design, and/or distributed system ...
Sr. Systems Engineer, Prime Air
Seattle, WA · On-site
$118K - $162K/yr
Geospatial engineering, Weather Science, Distributed Systems, Flight Decks, or Traffic Management. - Experience in cloud based software development, system design, and/or distributed system ...
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 ...
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 ...
Senior Systems Engineer
$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 ...
Senior Systems Engineer
$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 ...
Distributed Systems Engineer information
See Seattle, WA salary details
$60.9K - $72.6K
2% of jobs
$72.6K - $84.4K
4% of jobs
$84.4K - $96.1K
7% of jobs
$96.1K - $107.9K
9% of jobs
$111.1K is the 25th percentile. Wages below this are outliers.
$107.9K - $119.6K
10% of jobs
$119.6K - $131.3K
7% of jobs
$131.3K - $143.1K
10% of jobs
The median wage is $145K / yr.
$143.1K - $154.8K
6% of jobs
$154.8K - $166.6K
3% of jobs
$177.9K is the 75th percentile. Wages above this are outliers.
$166.6K - $178.3K
17% of jobs
$178.3K - $190.1K
24% of jobs
$60.9K
$144.8K
$190.1K
How much do distributed systems engineer jobs pay per year?
As of Jun 30, 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 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, 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:
- Infrastructure Engineer
- Aws Cloud Practitioner
- Senior Distributed Systems Engineer
- Work From Home Cloud Infrastructure Engineer
- Remote Aws Cloud
- Microsoft Systems Engineer
- Weekday Google Cloud Platform Developer
- Linux Network Engineer On Call
- Remote Avionics Systems Engineer
- Freelance Autonomous Underwater Vehicle
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:
Full-time
Posted yesterday
Key responsibilities
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.
Job description
Job Summary:
FieldAI is a company focused on building risk-aware, reliable AI systems for robotics. They are seeking a Senior / Staff ML Systems Engineer to architect and build distributed infrastructure for large-scale machine learning workflows, enabling efficient development and operation of production-grade systems.
Responsibilities:
• 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.
Qualifications:
Required:
• 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.
Preferred:
• 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.
Company:
FieldAI is building general robot intelligence for the physical world. Founded in 2023, the company is headquartered in Mission Viejo, USA, with a team of 201-500 employees. The company is currently Growth Stage.
FieldAI is a company focused on building risk-aware, reliable AI systems for robotics. They are seeking a Senior / Staff ML Systems Engineer to architect and build distributed infrastructure for large-scale machine learning workflows, enabling efficient development and operation of production-grade systems.
Responsibilities:
• 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.
Qualifications:
Required:
• 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.
Preferred:
• 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.
Company:
FieldAI is building general robot intelligence for the physical world. Founded in 2023, the company is headquartered in Mission Viejo, USA, with a team of 201-500 employees. The company is currently Growth Stage.