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Parallel Computing Jobs in Illinois (NOW HIRING)

HPC Systems Engineer

Chicago, IL · On-site

$150K - $200K/yr

... computing (HPC), including parallel filesystems (e.g., Lustre, GPFS), batch systems (e.g., Slurm, Grid Engine), and high-performance network interconnects experience is a plus, but not required * 5+ ...

Other duties as assigned or needed Skills You'll Need: * 5+ years of professional experience in high performance computing (HPC), including parallel filesystems (e.g., Lustre, GPFS), batch systems (e ...

HPC Systems Engineer

Chicago, IL · On-site

$150K - $200K/yr

Other duties as assigned or needed Skills You'll Need: * 5+ years of professional experience in high performance computing (HPC), including parallel filesystems (e.g., Lustre, GPFS), batch systems (e ...

C++ Software Engineer

Chicago, IL · On-site +1

$175K - $300K/yr

Experience with parallel, concurrent, and multi-threaded programming * Prefer experience with low-latency computing and hardware-level design * Experience with Git, SVN, Mercurial Benefits and Perks

... computing environment. * Experience provisioning and managing bare-metal infrastructure and data centers, not just cloud-native environments. * Familiarity with high-performance / parallel storage ...

Showing results 21-40

Parallel Computing information

See Illinois salary details

$24.2K

$50.7K

$87.7K

How much do parallel computing jobs pay per year?

As of Sep 14, 2026, the average yearly pay for parallel computing in Illinois is $50,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,800.00 and $57,700.00 per year, depending on experience, location, and employer.

What is parallel computing?

Parallel computing is a type of computation where many calculations or processes are carried out simultaneously, leveraging multiple processors or computers to solve complex problems more efficiently. It divides large tasks into smaller ones that can be executed concurrently, significantly speeding up processing time. Commonly used in scientific research, data analysis, and engineering, parallel computing is essential for handling large-scale simulations and big data applications.

What are some common challenges faced by professionals working in parallel computing roles?

Professionals in parallel computing often encounter challenges such as efficiently dividing complex tasks among multiple processors and minimizing communication overhead between them. Debugging and optimizing performance across parallel architectures can be difficult, as issues like race conditions and load imbalances frequently arise. Additionally, staying current with evolving hardware technologies and parallel programming frameworks is essential to ensure solutions remain efficient and scalable. Collaborating with cross-functional teams, such as data scientists and system architects, is also crucial for integrating parallel solutions into larger projects.

What are the key skills and qualifications needed to thrive as a parallel computing specialist, and why are they important?

To thrive as a Parallel Computing Specialist, you need strong knowledge of computer architecture, parallel algorithms, and experience with programming languages such as C/C++, Python, and frameworks like MPI or OpenMP, often supported by a degree in computer science or a related field. Familiarity with high-performance computing (HPC) environments, GPU programming (CUDA, OpenCL), and cloud-based parallel processing systems is typically required. Analytical thinking, problem-solving abilities, and effective collaboration are crucial soft skills in this role. These skills are vital for efficiently designing, optimizing, and implementing solutions that leverage parallelism to significantly accelerate computational tasks.

What is the difference between Parallel Computing vs Data Analyst?

AspectParallel ComputingData Analyst
Required CredentialsComputer Science or Engineering degree, programming skillsStatistics, Data Science, or related degree, analytical skills
Work EnvironmentResearch labs, tech companies, high-performance computing centersBusiness, finance, healthcare, corporate offices
Industry UsageTechnology, research, scientific computingBusiness intelligence, market analysis, reporting

While Parallel Computing focuses on developing algorithms to process large data sets efficiently across multiple processors, Data Analysts interpret data to provide actionable insights. Both roles require strong technical skills but serve different purposes: one enhances computational performance, the other informs business decisions.

Is parallel computing hard?

Parallel computing as a job involves designing and managing systems that perform multiple calculations simultaneously, which requires strong problem-solving skills, knowledge of algorithms, and proficiency with programming tools like MPI or OpenMP. The difficulty depends on the complexity of tasks and the level of expertise, but it generally involves understanding concurrency, synchronization, and performance optimization. Gaining experience through coursework, certifications, and hands-on projects can help reduce the learning curve.

What are popular job titles related to Parallel Computing jobs in Illinois?

For Parallel Computing jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Parallel Computing jobs in Illinois look for?

The top searched job categories for Parallel Computing jobs in Illinois are:

Infographic showing various Parallel Computing job openings in Illinois as of August 2026, with employment types broken down into 40% Full Time, and 60% Contract. Highlights an 100% In-person job distribution, with an average salary of $50,738 per year, or $24.4 per hour.

Principal, Solution Architecture

Chicago, IL • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 days ago


Job description

Solution Architect

Join the Options Clearing Corporation (OCC) as a Solution Architect to design and lead the next generation of OCC’s clearing system, driving digital transformation across capital markets.

Responsibilities
  • Design the applications’ architecture across distributed and enterprise technology platforms, leveraging event‑driven architecture, publish/subscribe messaging, and microservices.
  • Define and enforce architectural standards, patterns, and best practices across engineering teams.
  • Design streaming and batch‑based systems that support both real‑time and scheduled data flow.
  • Shape and guide the architecture of message‑based systems using Kafka or similar platforms to enable reliable, decoupled, event‑driven communication.
  • Develop and oversee data architecture and integration strategies spanning streaming, batch, and message‑based processing.
  • Own end‑to‑end solution architecture from ideation through implementation, documenting decisions and system diagrams.
  • Guide the development and deployment of distributed, cloud‑native services, ensuring resilience, scalability, and cost‑efficiency.
  • Collaborate with DevOps, platform engineering, and security teams to ensure architectures are operable, resilient, and aligned with organizational standards.
  • Review designs and code to ensure alignment with architectural standards, security requirements, and regulatory/compliance needs.
  • Troubleshoot and resolve complex, cross‑system issues across application, infrastructure, messaging, and data layers.
  • Partner with engineering, data, and business teams to translate business requirements into robust, scalable technical solutions.
  • Translate complex architectural decisions and trade‑offs into clear, actionable insights for business stakeholders and non‑technical audiences.
  • Evaluate emerging tools, frameworks, and technologies, and provide recommendations for adoption.
  • Mentor engineering teams on architectural best practices, distributed systems, event‑driven and batch processing design.
Qualifications
  • Demonstrated experience in event‑driven and message‑based systems, transaction processing systems, distributed and parallel computing.
  • Solid experience designing application architectures across distributed and enterprise technology platforms, including microservices and streaming or batch‑based applications.
  • Experience with projects involving complex integration of disparate technologies/platforms and data.
  • Experience architecting large‑scale distributed systems.
  • Architect Kubernetes‑based deployment topologies for stateless services and on‑demand jobs, including horizontal pod autoscaling, multi‑AZ resilience, and cross‑region/on‑prem failover and disaster recovery strategies.
  • Fluent in object‑oriented design, industry best practices, software patterns, and architecture principles.
  • Experience defining and documenting architecture strategies, designs, and requirements across all enterprise architecture domains.
  • Experience defining non‑functional requirements (NFRs) including performance, scalability, availability, and security, and ensuring application architecture satisfies them.
  • Highly motivated with a strong sense of ownership of work and projects.
  • Excellent oral and written communication skills.
Technical Skills
  • Software development experience in Java, Python, or C#, including building high‑throughput, low‑latency services for data‑intensive or transaction‑oriented systems.
  • Strong knowledge of Kafka or other messaging/streaming systems, including topic design, partitioning strategies, and producer/consumer patterns.
  • Fluent in object‑oriented design principles, software design patterns, and modern architecture practices (microservices, event‑driven architecture, domain‑driven design).
  • Knowledge of identity and access management using OAuth2/OIDC flows, JWT‑based token validation, and integration with identity providers (ForgeRock, SailPoint).
  • Knowledge of schema management and data serialization formats, preferably Protocol Buffers (Protobuf), including schema evolution.
  • Understanding of data lake‑house architecture and table formats such as Apache Iceberg.
  • Familiarity with Infrastructure as Code principles and tooling, preferably Terraform.
  • Working knowledge of DevOps tooling and practices such as Git, Jenkins, Docker, Artifactory, ArgoCD, and others.
  • Experience working with Cloud ecosystems (AWS, PaaS, K8s).
Minimum Qualifications
  • BS degree in Computer Science, a similar technical field, or equivalent practical experience.
  • 10+ years of relevant work experience.
Preferred Qualifications
  • 6+ years of work experience in the capital markets industry.
Benefits
  • Hybrid work environment, up to 2 days per week of remote work.
  • Tuition reimbursement to support continued education.
  • Student loan repayment assistance.
  • Technology stipend for remote work.
  • Generous PTO and parental leave.
  • 401(k) with employer match.
  • Competitive medical, dental, and vision coverage.
Salary

$175,100.00 – $282,800.00 with an incentive range of 23% to 30%.

Equal Opportunity Employer

OCC is an Equal Opportunity Employer and is committed to diversity, equity, and inclusion. OCC provides equal employment opportunities to all employees and applicants for employment without regard to race, color, national origin, citizenship status, sex, sexual orientation, gender identity, disability, age, marital status, religion, veteran status, or any other characteristics protected by applicable federal, state, or local laws.

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