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Senior Distributed Systems Engineer Jobs in Riverside, CA

DZYNE Technologies

Senior Systems Engineer

Irvine, CA · On-site

$130K - $170K/yr

Senior Systems Engineer Location: Irvine, CA Work Arrangement: On-Site Position Summary As a Senior Systems Engineer, you will lead the systems engineering activities for Long Endurance ISR UAS ...

DZYNE Technologies LLC.

Senior Systems Engineer

Irvine, CA · On-site

$130K - $170K/yr

Senior Systems Engineer Location: Irvine, CA Work Arrangement: On-Site Position Summary As a Senior Systems Engineer, you will lead the systems engineering activities for Long Endurance ISR UAS ...

Prescient Edge

Senior Systems Engineer

Riverside, CA · On-site

$109K - $149K/yr

Job Title Senior Systems Engineer Location Riverside, CA US (Primary) Category Research, Development, and Engineering Job Type Full-Time Career Level Staff Education Bachelor's Degree Travel None ...

AVEVA Denmark

Power Systems Engineer

Irvine, CA · On-site

$65 - $108/hr

Job Title Power System Engineer Job Location: Irvine, CA Job Type: Full-time / Hybrid Position ... Proficiency in modeling for transmission and distribution power systems * Perform power flow, short ...

ETAP

Power Systems Engineer

Irvine, CA · On-site

Power System Engineer Job Location: Irvine, CA Job Type: Full-time / Hybrid Position Summary ETAP ... Proficiency in modeling for transmission and distribution power systems * Perform power flow, short ...

Aveva

Power Systems Engineer

Irvine, CA · On-site

Power System Engineer Job Location: Irvine, CA Job Type: Full-time / Hybrid Position Summary ETAP ... Proficiency in modeling for transmission and distribution power systems * Perform power flow, short ...

Diality Inc

Senior Systems Engineer

Irvine, CA · On-site

$120K - $133K/yr

As a Senior Systems Engineer, you will leverage your extensive expertise to drive the design, development, and validation of complex systems, ensuring compliance with regulatory standards and ...

Diality

Senior Systems Engineer

Irvine, CA · On-site

$120K - $133K/yr

As a Senior Systems Engineer, you will leverage your extensive expertise to drive the design, development, and validation of complex systems, ensuring compliance with regulatory standards and ...

1872 Consulting

Senior Systems Engineer

Irvine, CA · On-site

$112K - $153K/yr

Senior Systems EngineerSenior Systems Engineer opening in Irvine, CA with a stable, global enterprise (onsite position). On call rotation once every 5 weeks. No travel.Systems Support and ...

1872 Consulting

Senior Systems Engineer

Irvine, CA · On-site

$112K - $153K/yr

Senior Systems EngineerSenior Systems Engineer opening in Irvine, CA with a stable, global enterprise (onsite position). On call rotation once every 5 weeks. No travel.Systems Support and ...

NextDeavor Inc.

Systems Engineer

Irvine, CA · On-site

$54.93 - $68.66/hr

Systems Engineer Full-time Irvine, CA, US Exclusive confidential search -- details shared with ... Strong written and verbal communication skills; ability to present complex topics to senior ...

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All JobsDistributed Systems Engineer JobsSenior Distributed Systems Engineer JobsSenior Distributed Systems Engineer Jobs in Riverside, CA

Senior Distributed Systems Engineer information

See Riverside, CA salary details

$58.4K

$130.1K

$183.6K

How much do senior distributed systems engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for senior distributed systems engineer in Riverside, CA is $130,129.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,000.00 and $149,200.00 per year, depending on experience, location, and employer.

What is a senior distributed systems engineer?

Senior Distributed Systems Engineers are experienced professionals who design, build, and maintain large-scale computing systems that run across multiple machines or locations. They focus on ensuring reliability, scalability, and performance of distributed applications, often dealing with challenges like data consistency, fault tolerance, and network latency. These engineers typically have deep expertise in distributed computing principles, programming languages, and cloud infrastructure. They also mentor junior team members and help architect robust solutions for complex technical problems.

What are the key skills and qualifications needed to thrive as a senior distributed systems engineer?

A Senior Distributed Systems Engineer requires deep expertise in computer science fundamentals, scalable system architecture, and proficiency in programming languages such as Java, Go, or Python, often supported by a relevant degree and significant experience in distributed systems. Familiarity with tools like Kubernetes, Docker, Kafka, and cloud platforms (AWS, GCP, or Azure) is typically expected, along with knowledge of monitoring and CI/CD pipelines. Strong problem-solving, communication, and leadership skills help in tackling complex engineering challenges and collaborating across teams. These skills are crucial for designing robust, scalable, and reliable systems that support organizational growth and high availability.

What are some common challenges senior distributed systems engineers face when designing scalable systems?

Senior Distributed Systems Engineers often encounter challenges such as managing data consistency, ensuring fault tolerance, and minimizing latency across multiple nodes. Balancing trade-offs between availability and partition tolerance (as outlined by the CAP theorem) is a frequent consideration. Additionally, coordinating between development and operations teams to maintain system reliability and efficiently resolve issues that arise in production environments is crucial. Strong communication skills and a deep understanding of distributed architectures help address these complexities effectively.

What is the difference between Senior Distributed Systems Engineer vs Cloud Solutions Architect?

AspectSenior Distributed Systems EngineerCloud Solutions Architect
CredentialsBachelor's/Master's in CS or related, experience with distributed systemsBachelor's/Master's in CS, IT, or related, cloud certifications (AWS, Azure)
Work EnvironmentDesigning, developing, and maintaining distributed systems in tech companiesDesigning cloud infrastructure solutions for clients or internal teams
Industry UsageTech, finance, e-commerce, and enterprise sectorsIT consulting, cloud service providers, enterprise IT departments

The Senior Distributed Systems Engineer focuses on building and optimizing distributed computing systems, while the Cloud Solutions Architect designs cloud infrastructure solutions. Both roles require technical expertise and often overlap in cloud environments, but their primary responsibilities differ in scope and focus.

What are popular job titles related to Senior Distributed Systems Engineer jobs in Riverside, CA?

For Senior Distributed Systems Engineer jobs in Riverside, CA, the most frequently searched job titles are:

What job categories do people searching Senior Distributed Systems Engineer jobs in Riverside, CA look for?

The top searched job categories for Senior Distributed Systems Engineer jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Senior Distributed Systems Engineer jobs?

Cities near Riverside, CA with the most Senior Distributed Systems Engineer job openings:

Senior Distributed Systems Engineer jobs near you
Infographic showing various Senior Distributed Systems Engineer job openings in Riverside, CA as of August 2026, with employment types broken down into 83% Full Time, 13% Part Time, and 4% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $130,129 per year, or $62.6 per hour.

Staff ML Systems Engineer, Distributed Systems

FieldAI

Irvine, CA • On-site

Full-time

Re-posted 24 days ago

Job description

Job Summary:
FieldAI is a company that specializes in building reliable, field-ready 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, focusing on scalable systems that support data processing and model training.
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.

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