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High Performance Computing Hpc Jobs in New Jersey

QCi

Senior Engineer, Quantum Algorithms

Hoboken, NJ · On-site

Skills C++, Quantum Algorithms, High Performance Computing (HPC), Algorithm Design, Mathematical Optimization,, Multi-threading, Linux, CMake, Python, Performance Profiling, Hardware Abstraction ...

QCi

Skills C++, Quantum Algorithms, High Performance Computing (HPC), Algorithm Design, Mathematical Optimization,, Multi-threading, Linux, CMake, Python, Performance Profiling, Hardware Abstraction ...

Zifo

Senior Cloud Engineer

Warren, NJ · On-site

$58 - $77.25/hr

The Senior Cloud Engineer is responsible for designing, implementing, and managing large-scale high-performance computing (HPC) platforms on AWS for scientific and research-driven workloads. This ...

QCi

Technical Account Manager

Hoboken, NJ · On-site

Monitor industry trends across photonics, high-performance computing, and optimization technologies ... Exposure to optimization problems, HPC workflows, or computational modeling environments.

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High Performance Computing Hpc information

See New Jersey salary details

$33K

$69.3K

$113.7K

How much do high performance computing hpc jobs pay per year?

As of Jul 31, 2026, the average yearly pay for high performance computing hpc in New Jersey is $69,288.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,800.00 and $84,300.00 per year, depending on experience, location, and employer.

What is the difference between High Performance Computing Hpc vs Data Scientist?

AspectHigh Performance Computing (HPC)Data Scientist
Required credentialsDegree in Computer Science, Engineering, or related fields; often certifications in parallel computing or HPC systemsDegree in Data Science, Statistics, Computer Science, or related fields; certifications in data analysis or machine learning
Work environmentSupercomputing centers, research labs, large enterprises with high computational needsTech companies, finance, healthcare, research institutions, often in office or remote settings
Industry usageScientific research, simulations, modeling, large-scale data processingData analysis, predictive modeling, machine learning, business insights

While both roles involve working with large datasets and complex computations, HPC specialists focus on designing and maintaining high-performance computing systems for scientific and engineering tasks. Data scientists analyze data to extract insights and build models. The roles often overlap in data processing but differ in technical focus and environment.

What are some common challenges faced by professionals working in High Performance Computing (HPC) environments?

Professionals in HPC roles often encounter challenges such as optimizing code for parallel processing, managing complex and rapidly evolving hardware architectures, and troubleshooting large-scale distributed systems. Collaborating closely with researchers and domain experts is also essential to ensure that computational resources are used efficiently and effectively. Keeping up with advances in both hardware and software, as well as balancing multiple projects with tight deadlines, are typical aspects of the HPC work environment.

What is High Performance Computing (HPC)?

High Performance Computing (HPC) refers to the use of supercomputers and parallel processing techniques to solve complex computational problems quickly and efficiently. HPC systems combine the power of multiple processors to perform billions or even trillions of calculations per second, making them essential for scientific research, engineering simulations, data analytics, and other demanding tasks. These systems are used in fields such as weather forecasting, molecular modeling, financial modeling, and artificial intelligence. By leveraging HPC, organizations can tackle problems that are too large or complex for standard computers.

What are the key skills and qualifications needed to thrive as a High Performance Computing (HPC) specialist, and why are they important?

To thrive as a High Performance Computing (HPC) specialist, you need a solid background in computer science or engineering, strong programming skills (especially in languages like C, C++, or Python), and expertise in parallel computing and Linux systems. Familiarity with cluster management tools, job schedulers (e.g., SLURM or PBS), and experience with HPC libraries and accelerators such as MPI, OpenMP, and GPU programming are typically required. Excellent problem-solving abilities, teamwork, and effective communication skills help you collaborate with researchers and resolve complex technical challenges. These competencies are vital for optimizing computational workflows, maintaining robust systems, and enabling advanced scientific or industrial research.
What are popular job titles related to High Performance Computing Hpc jobs in New Jersey? For High Performance Computing Hpc jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching High Performance Computing Hpc jobs in New Jersey look for? The top searched job categories for High Performance Computing Hpc jobs in New Jersey are:
High Performance Computing Hpc jobs near you
Infographic showing various High Performance Computing Hpc job openings in New Jersey as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $69,288 per year, or $33.3 per hour.

Lead Systems Engineer (HPC)

Princeton University

Princeton, NJ • On-site

$135K - $150K/yr

Full-time

Re-posted 26 days ago

Princeton University rating

9.0

Company rating: 9.0 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

26th of 614 rated colleges and universities

Job description

Overview
The Lead Systems Engineer for High Performance Computing (HPC) and Artificial Intelligence (AI) works as part of the Advanced Systems team within Research Computing that supports the hardware and system-level software on the University's centralized high-performance computing and other computing for research systems. The Lead Systems Engineer is responsible for engaging with faculty, researchers, vendors, and other information technology (IT) staff to specify, design, install, and administer computing for research systems while also providing insight into trends and technologies supporting the advancement of AI research. The Lead Systems Engineer is also expected to be in tune to trends in computational research and will be asked to evaluate, pilot, and implement systems that advance Princeton's HPC and AI technologies enhancing Research Computing services. The Lead Systems Engineer serves as an expert for HPC and AI hardware and software and helps researchers troubleshoot system level problems with software, data, and job submission. This position requires one to work closely with colleagues at all levels of technical understanding in the Office of Information Technology (OIT) and University academic departments to provide timely and creative support for research computing. The Lead Systems Engineer is required to work well on teams and independently, and will be asked to lead initiatives within Advanced Systems, requiring only general supervision.
On-call rotation is a mandatory facet of this role, requiring infrequent off-hour and weekend duty.
Responsibilities
Operations:
  • Design, maintain, troubleshoot, and refine advanced HPC/AI cluster infrastructure including high-performance interconnects, cluster schedulers, and configuration management across research systems.
  • Partner with colleagues in Advanced Data and Storage Management to align designs for scratch filesystems and data management with cluster designs.
  • Develop data-transfer pathways and networks to support AI-driven computing workloads.
  • Establish and maintain best practices for cluster management and usage to support AI-driven workloads.
  • Develop documentation for users and technical staff that can be used by the larger community.
  • Develop, enhance, and expand monitoring infrastructure and related protocols for research computing systems.
  • Plan and implement scheduled maintenance of operations, including during off hours.
  • Perform other tasks as assigned.

Technical Leadership:
  • Define and drive the institutional technical strategy for advanced AI and data-intensive HPC.
  • Bring creativity, foresight, and mature professional judgment in anticipating and solving novel and complex problems, in determining project objectives and requirements, and in developing standards and governance for all research computing platforms.
  • Leveraging expertise in AI technologies, identify, evaluate, and pilot researcher-facing systems that enable the acceleration of research using AI.
  • Lead the implementation and expand adoption of modern, automation-driven infrastructure and cluster management practices.
  • Promote institution-wide collaboration as the community expert advising and working with faculty, researchers and vendors on emerging trends and challenges in AI-enabled research computing.
  • Cultivate a collaborative, knowledge-sharing environment by providing technical mentorship to systems specialists and analysts by sharing designs and operational expertise across data systems and HPC/AI infrastructure.
  • Contribute to the strategic vision for HPC/AI systems; Advise senior leadership and stakeholders on strategic investments, risks, and opportunities related to research infrastructure.

Troubleshooting and Problem Resolution:
  • Monitor HPC clusters, networks, and storage systems for abnormalities, and resolve issues.
  • Analyze and solve problems in Linux and HPC/AI computing environments with software, data, and job submissions.
  • Use scripting and programming tools to troubleshoot issues.

Qualifications
Essential Qualifications:
  • 10+ years of strong experience managing advanced research computing systems.
  • Strong expertise with Linux system administration, installation, and troubleshooting.
  • Advanced experience writing scripts in languages such as bash, Python and/or Perl.
  • Proficient in managing networking in HPC environments.
  • Strong experience managing software in an advanced research computing environment.
  • Experience supporting scheduling and managing jobs (SLURM) in large-scale computing environments.
  • Strong oral and written communication skills, with the ability to proactively engage peers and communicate effectively across a diverse stakeholder community.
  • Strong ability to solve complex and system infrastructure problems, and share expertise with colleagues at all levels.
  • Demonstrated ability to collaborate across teams to solve systems and infrastructure challenges, aligning day-to-day operational needs with longer-term technical and organizational goals as technologies evolve.
  • When provided access to personal, proprietary and/or otherwise confidential data, maintain such data in the strictest confidence and follow procedures to ensure the privacy, security, and proper use of data.
  • Education: Bachelors degree in a related field or equivalent experience.

Preferred Qualifications:
  • Experience working in an academic and research settings.
  • Experience supporting AI-driven research in open and secure computing environments.
  • Familiarity using and administering data-transfer technologies such as Globus that facilitate the transfer of large datasets.
  • Experience using and supporting parallel file systems that are commonly used in HPC/AI systems.
  • Experience supporting unstructured data in HPC/AI environments.

Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.
The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.
If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.
The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
Standard Weekly Hours
36.25
Eligible for Overtime
No
Benefits Eligible
Yes
Probationary Period
180 days
Essential Services Personnel (see policy for detail)
No
Physical Capacity Exam Required
No
Valid Driver's License Required
No
Experience Level
Director
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Salary Range
$135,000 to $150,000

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