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Parallel Jobs in Sunnyvale, CA (NOW HIRING)

Apple Inc.

Software Engineer, Algorithms (SDE)

Cupertino, CA · On-site

$150.40 - $277.60/hr

While porting, you will look for opportunities to break algorithms into modular blocks, graphs and sub‑graphs, that can run in parallel to reduce execution time. You will collaborate closely with ...

Apple

Software Engineer, Algorithms (SDE)

Cupertino, CA

$150K - $277K/yr

While porting, you will look for opportunities to break algorithms into modular blocks, graphs and sub-graphs, that can run in parallel to reduce execution time. You will collaborate closely with ...

Intelliswift - An LTTS Company

DevOps Engineer I

Pleasanton, CA · On-site

$58.50 - $80.25/hr

Intelliswift - An LTTS Company is seeking a DevOps Engineer I to design and develop parallel computing algorithms and tools. The role involves managing the life-cycle of HPC products and researching ...

Substrate

Technical Program Manager

San Francisco, CA · On-site

$150K - $275K/yr

This role requires managing parallel workstreams where hardware development, R&D, manufacturing, and scientific validation all happen simultaneously with interdependent deliverables. Responsibilities

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Showing results 41-60

All JobsParallel JobsParallel Jobs in Sunnyvale, CA

Parallel information

See Sunnyvale, CA salary details

$29.3K

$61.5K

$106.2K

How much do parallel jobs pay per year?

As of Sep 5, 2026, the average yearly pay for parallel in Sunnyvale, CA is $61,452.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,900.00 and $69,800.00 per year, depending on experience, location, and employer.

What is a parallel?

In the context of computing and technology, 'Parallel jobs' refer to tasks or processes that are executed simultaneously across multiple processors or computers. This approach is commonly used in high-performance computing (HPC), data processing, and scientific research to speed up complex computations by breaking them into smaller, concurrent tasks. Parallel jobs can significantly reduce the time required to process large datasets or perform intensive calculations. They are managed using parallel computing frameworks and often require specialized software and hardware to coordinate the execution of multiple processes. Understanding how to design and manage parallel jobs is essential for roles in data science, engineering, and research fields.

What skills and qualifications are needed to thrive as a parallel?

To thrive as a Parallel Computing Engineer, you need a strong background in computer science, mathematics, and parallel algorithms, often supported by a relevant degree. Proficiency with parallel programming languages (such as CUDA, OpenMP, or MPI), high-performance computing (HPC) clusters, and debugging tools is essential. Strong analytical thinking, collaborative teamwork, and effective problem-solving skills help you stand out in this field. These skills are vital for optimizing computational processes and ensuring efficient, scalable solutions in complex computing environments.

What are common challenges faced by professionals working in parallel computing roles, and how can they be addressed?

Professionals in parallel computing roles often encounter challenges such as debugging complex, concurrent code and optimizing performance across multiple processors. These issues require a solid understanding of parallel algorithms and experience with tools designed for performance profiling and debugging. Collaboration with team members is essential, as projects typically involve working closely with software engineers, system architects, and hardware specialists. To address these challenges, it's helpful to stay current with best practices, participate in code reviews, and leverage community resources and documentation.

What is the difference between Parallel vs Network Engineer?

AspectParallelNetwork Engineer
Required CertificationsCompTIA A+, Cisco CCNA, Network+CCNA, CCNP, CompTIA Network+
Work EnvironmentData centers, server rooms, cloud environmentsCorporate offices, data centers, ISPs
Industry UsageIT, cloud services, data managementTelecommunications, IT, enterprise networks
Common Search/ComparisonParallel vs Network Engineer

Parallel and Network Engineer roles share similar certifications and work environments, often overlapping in IT and data management sectors. However, Parallel roles focus more on parallel processing and computing tasks, while Network Engineers specialize in designing and maintaining network infrastructure. Understanding these differences helps job seekers identify the right career path based on their skills and interests.

What cities near Sunnyvale, CA are hiring for Parallel jobs?

Cities near Sunnyvale, CA with the most Parallel job openings:

Parallel jobs near you
Infographic showing various Parallel job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 2% As Needed, 79% Full Time, 15% Part Time, and 4% Contract. Highlights an 75% Physical, 5% Hybrid, and 20% Remote job distribution, with an average salary of $61,452 per year, or $29.5 per hour.

Cloud Storage Integration Engineer (Storage / Image / Registry)

Palo Alto Networks

San Jose, CA • On-site

Full-time

Posted 8 days ago

Key responsibilities

  • Design and integrate distributed / parallel file systems into the GPU cloud, optimized for AI training / inference I/O patterns.

  • Own end-to-end distributed-storage integration, including provisioning, mounting, multi-tenant isolation, quota, and lifecycle management.

  • Own golden images, templates, GPU drivers / CUDA, and the container / image registry, including versioned release and multi-region distribution.

Job description

About Bitdeer Technologies Group

Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure.

Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence.

Headquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.
To learn more, visit https://ir.bitdeer.com/

Position Overview

GPU training and inference at 10,000+ GPU, multi-region scale depend on high-throughput, low-latency storage that can sustain massive parallel I/O. We are looking for an engineer who deeply understands distributed file systems and can integrate distributed / parallel storage systems into our GPU cloud - covering performance, multi-tenancy, and reliability - while also owning the image / driver / registry pipeline on the node-delivery critical path.

Key Responsibilities

  • Design and integrate distributed / parallel file systems (e.g. Ceph, Lustre, GPFS / Spectrum Scale, BeeGFS, JuiceFS) into the GPU cloud, optimized for AI training / inference I/O patterns.
  • Own end-to-end distributed-storage integration: provisioning, mounting, multi-tenant isolation, quota, and lifecycle within the platform / control plane.
  • Tune storage throughput and latency for large-scale parallel access (dataset loading, checkpointing); benchmark across GPU SKUs and workloads.
  • Architect multi-region storage: data locality, replication / consistency, durability (failure domains), and cross-region access.
  • Own golden images, templates, GPU drivers / CUDA, and the container / image registry, including versioned release and multi-region distribution. (Secondary scope.)
  • Build monitoring, capacity planning, and runbooks; eliminate single points of failure.
  • Partner with Compute (delivery), Network (storage fabric / RDMA), and Control Plane (provisioning / quota) teams.

Job Requirement:

  • 3+ years (Senior 6+) in storage engineering or platform infrastructure, with hands-on distributed / parallel file system experience.
  • Strong understanding of distributed file system internals - data / metadata separation, replication, consistency models, POSIX vs object semantics.
  • Proven experience integrating and operating distributed storage in production (e.g. Ceph, Lustre, GPFS / Spectrum Scale, BeeGFS, JuiceFS, MinIO).
  • Performance tuning for high-throughput / parallel I/O; familiarity with NVMe, RDMA / RoCE storage networking, and caching is a strong plus.
  • Strong Linux systems depth and automation skills (Python / Go, CI / CD).
  • HPC / AI storage or multi-region storage experience a strong plus.

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Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, color, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.

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