... performance specifications generate feasible chamber geometries, showerhead/baffle designs, and ... Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments ...
... performance specifications generate feasible chamber geometries, showerhead/baffle designs, and ... Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments ...
... HPC networking, and performance tuning. * Direct the implementation and maintenance of CI/CD pipelines supporting model training, model deployment, and data-intensive workflows. * Guide engineers on ...
... HPC networking, and performance tuning. * Direct the implementation and maintenance of CI/CD pipelines supporting model training, model deployment, and data-intensive workflows. * Guide engineers on ...
... HPC networking, and performance tuning. * Direct the implementation and maintenance of CI/CD pipelines supporting model training, model deployment, and data-intensive workflows. * Guide engineers on ...
... HPC networking, and performance tuning. * Direct the implementation and maintenance of CI/CD pipelines supporting model training, model deployment, and data-intensive workflows. * Guide engineers on ...
... performance computing systems, guiding engineering teams and managing project execution across ... MLOps, and HPC workloads. • Oversee GPU‑enabled compute clusters, HPC networking, and ...
... performance computing systems, guiding engineering teams and managing project execution across ... MLOps, and HPC workloads. • Oversee GPU‑enabled compute clusters, HPC networking, and ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
... HPC networking, and performance tuning. * Direct the implementation and maintenance of CI/CD pipelines supporting model training, model deployment, and data‑intensive workflows. * Guide engineers ...
... HPC networking, and performance tuning. * Direct the implementation and maintenance of CI/CD pipelines supporting model training, model deployment, and data‑intensive workflows. * Guide engineers ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
... HPC networking, and performance tuning. * Direct the implementation and maintenance of CI/CD pipelines supporting model training, model deployment, and data‑intensive workflows. * Guide engineers ...
... HPC networking, and performance tuning. * Direct the implementation and maintenance of CI/CD pipelines supporting model training, model deployment, and data‑intensive workflows. * Guide engineers ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Monitor system health, resource utilization, performance, and capacity across Linux and HPC ... Collaborate with research, engineering, infrastructure, and application teams to support ...
Hpc Performance Engineer information
What is an HPC performance engineer?
HPC Performance Engineers are specialists who focus on optimizing the performance of high-performance computing (HPC) systems and applications. They analyze system bottlenecks, tune software and hardware configurations, and work with researchers and developers to ensure applications run efficiently on supercomputers or large computing clusters. Their work is essential for maximizing computational resources and improving the speed and scalability of scientific, engineering, or data-intensive workloads.
What are the key skills and qualifications needed to thrive as an HPC performance engineer?
To thrive as an HPC Performance Engineer, you need a strong background in computer science or engineering, with expertise in parallel programming, high-performance computing architectures, and performance analysis. Familiarity with tools like MPI, OpenMP, profiling software (e.g., Intel VTune, GNU gprof), and experience with job schedulers and Linux systems are essential. Analytical thinking, problem-solving, and effective communication are crucial soft skills for identifying bottlenecks and collaborating with multidisciplinary teams. These skills are vital for optimizing computational workflows, maximizing resource utilization, and driving efficiency in complex HPC environments.
What are the typical challenges HPC performance engineers face when optimizing large-scale computational workloads?
HPC Performance Engineers often encounter challenges such as identifying bottlenecks in parallel code, managing resource contention, and optimizing data movement across distributed systems. They must balance maximizing throughput with minimizing latency, all while ensuring applications scale efficiently as cluster sizes grow. Collaboration with software developers, system administrators, and research teams is common to align application requirements with hardware capabilities and to implement effective performance improvements.
What is the difference between Hpc Performance Engineer vs Hpc System Administrator?
| Aspect | Hpc Performance Engineer | Hpc System Administrator |
|---|---|---|
| Primary Focus | Optimizing HPC system performance and efficiency | Managing and maintaining HPC infrastructure |
| Skills & Certifications | Performance tuning, parallel computing, Linux, scripting | System setup, network management, user support |
| Work Environment | Research labs, data centers, high-performance computing facilities | Data centers, IT departments, research institutions |
| Common Tasks | Performance analysis, bottleneck resolution, code optimization | System installation, user account management, hardware troubleshooting |
The Hpc Performance Engineer focuses on enhancing system performance and efficiency, often working on optimization and tuning. In contrast, the Hpc System Administrator manages the day-to-day operation and maintenance of HPC systems. Both roles are essential in high-performance computing environments but serve different core functions.
What cities in Florida are hiring for Hpc Performance Engineer jobs?
Cities in Florida with the most Hpc Performance Engineer job openings:
Information Technology_USA - USA_Engineer
Jacksonville, FL • On-site
Real Soft, Inc.
• IT Services • 501 - 1,000 employees501 - 1,000 employees
Contractor
This job post has expired today. Applications are no longer accepted.
Job description
**Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES B/T UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
MSP Owner: Deepa Narayanan
Location: Santa Clara CA
Duration: 6 Months
Gbams Number: 10680928
ONSITE ROLE
Local candidates preferred.
Ai Hardware Design Engineer
***NOTE: Experience for SciML R&D and exposure in Neural operators, PINNs etc. is required***
We are seeking an Ai Hardware Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and workflows for applications such as content creation, product design, and intelligent automation.
• Develop forward surrogate models for CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film-uniformity, step-coverage, particle behavior, and thermal outcomes.
• Implement inverse-design workflows where target performance specifications generate feasible chamber geometries, showerhead/baffle designs, and process conditions via generative or adjoint/topology-optimization methods.
• Build bi-directional models that infer optimal process parameters for a given geometry and recommend geometry modifications when process latitude is insufficient.
• Create high-fidelity digital twins combining physics-based solvers (CFD, plasma, heat transfer) with learned surrogate components for rapid design-space exploration.
• Platform & MLOps Infrastructure: Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments to deploy models efficiently.
• Develop robust multi-objective optimization and uncertainty-quantification workflows to ensure AI-generated designs are manufacturable, robust to variation, and compatible with downstream yield requirements.
• Collaborate with physicists, domain experts, and software engineers to validate that AI models comply with fundamental scientific laws.
•
Required Skills & Qualifications
• Education: Master's or Ph.D. in Computer Science, Computational/Electrical Engineering, AI/ML, or related field.
• Technical Expertise:
o Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
o Experience with generative AI (LLMs, diffusion models, graph-based models).
o Knowledge of computational materials methods (DFT, MD, phase-field modeling).
• Additional Skills:
o Familiarity with MLOps, HPC environments, and cloud deployment.
o Proven experience (code repos, publications) bridging simulation software, hardware design, and ML.
Skills: Digital : Python~Digital : Machine Learning
Experience Required: 6-8, Project Code :
ALL CAPS, NO SPACES B/T UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
MSP Owner: Deepa Narayanan
Location: Santa Clara CA
Duration: 6 Months
Gbams Number: 10680928
ONSITE ROLE
Local candidates preferred.
Ai Hardware Design Engineer
***NOTE: Experience for SciML R&D and exposure in Neural operators, PINNs etc. is required***
We are seeking an Ai Hardware Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and workflows for applications such as content creation, product design, and intelligent automation.
• Develop forward surrogate models for CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film-uniformity, step-coverage, particle behavior, and thermal outcomes.
• Implement inverse-design workflows where target performance specifications generate feasible chamber geometries, showerhead/baffle designs, and process conditions via generative or adjoint/topology-optimization methods.
• Build bi-directional models that infer optimal process parameters for a given geometry and recommend geometry modifications when process latitude is insufficient.
• Create high-fidelity digital twins combining physics-based solvers (CFD, plasma, heat transfer) with learned surrogate components for rapid design-space exploration.
• Platform & MLOps Infrastructure: Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments to deploy models efficiently.
• Develop robust multi-objective optimization and uncertainty-quantification workflows to ensure AI-generated designs are manufacturable, robust to variation, and compatible with downstream yield requirements.
• Collaborate with physicists, domain experts, and software engineers to validate that AI models comply with fundamental scientific laws.
•
Required Skills & Qualifications
• Education: Master's or Ph.D. in Computer Science, Computational/Electrical Engineering, AI/ML, or related field.
• Technical Expertise:
o Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
o Experience with generative AI (LLMs, diffusion models, graph-based models).
o Knowledge of computational materials methods (DFT, MD, phase-field modeling).
• Additional Skills:
o Familiarity with MLOps, HPC environments, and cloud deployment.
o Proven experience (code repos, publications) bridging simulation software, hardware design, and ML.
Skills: Digital : Python~Digital : Machine Learning
Experience Required: 6-8, Project Code :
About Real Soft
Sourced by ZipRecruiter
Industry
It services
Company size
501 - 1,000 Employees
Headquarters location
Monmouth Junction, NJ, US
Year founded
1991