Hpc Engineer Jobs for OPT Students
HPC Engineer jobs are a strong fit for F-1 OPT students with backgrounds in computer science, computational science, or engineering. Employers in national labs, research universities, and tech firms regularly hire for these roles, and the work typically qualifies for the 24-month STEM OPT extension.
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Get Access To All JobsINTRODUCTION
Headquartered in Silicon Valley, we are a newly established start-up, where a collective of visionary scientists, engineers, and entrepreneurs are dedicated to transforming the landscape of biology and medicine through the power of Generative AI. Our team comprises leading minds and innovators in AI and Biological Science, pushing the boundaries of what is possible. We are dreamers who reimagine a new paradigm for biology and medicine. We are committed to decoding biology holistically and enabling the next generation of life-transforming solutions. As the first mover in pan-modal Large Biological Models (LBM), we are pioneering a new era of biomedicine, with our LBM training leading to ground-breaking advancements and a transformative approach to healthcare. Our exceptionally strong R&D team and leadership in LLM and generative AI position us at the forefront of this revolutionary field. With headquarters in Silicon Valley, California, and a branch office in Paris, we are poised to make a global impact. Join us as we embark on this journey to redefine the future of biology and medicine through the transformative power of Generative AI.
ROLE AND RESPONSIBILITIES
- GPU Cluster Management: Design, deploy, and maintain high-performance GPU clusters, ensuring their stability, reliability, and scalability. Monitor and manage cluster resources to maximize utilization and efficiency
- Distributed/Parallel Training: Implement distributed computing techniques to enable parallel training of large deep learning models across multiple GPUs and nodes. Optimize data distribution and synchronization to achieve faster convergence and reduced training times
- Performance Optimization: Fine-tune GPU clusters and deep learning frameworks to achieve optimal performance for specific workloads. Identify and resolve performance bottlenecks through profiling and system analysis
- Deep Learning Framework Integration: Collaborate with data scientists and machine learning engineers to integrate distributed training capabilities into GenBio AI’s model development and deployment frameworks.
- Scalability and Resource Management: Ensure that the GPU clusters can scale effectively to handle increasing computational demands. Develop resource management strategies to prioritize and allocate computing resources based on project requirements.
- Troubleshooting and Support: Troubleshoot and resolve issues related to GPU clusters, distributed training, and performance anomalies. Provide technical support to users and resolve technical challenges efficiently
- Documentation: Create and maintain documentation related to GPU cluster configuration, distributed training workflows, and best practices to ensure knowledge sharing and seamless onboarding of new team members
BASIC QUALIFICATIONS
- Master’s or Ph.D. degree in computer science, or a related field with a focus on High-Performance Computing, Distributed Systems, or Deep Learning
- 2+ years proven experience in managing GPU clusters, including installation, configuration, and optimization
- Strong expertise in distributed deep learning and parallel training techniques
- Proficiency in popular deep learning frameworks like PyTorch, Megatron-LM, DeepSpeed, etc
- Programming skills in Python and experience with GPU-accelerated libraries (e.g., CUDA, cuDNN)
- Knowledge of performance profiling and optimization tools for HPC and deep learning
- Familiarity with resource management and scheduling systems (e.g., SLURM, Kubernetes)
- Strong background in distributed systems, cloud computing (AWS, GCP), and containerization (Docker, Kubernetes)
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. GenBio AI participates in the U.S. Department of Homeland Security’s E-Verify program to confirm the employment eligibility of all newly hired employees. For more information on E-Verify, please visit www.e-verify.gov. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
INTRODUCTION
Headquartered in Silicon Valley, we are a newly established start-up, where a collective of visionary scientists, engineers, and entrepreneurs are dedicated to transforming the landscape of biology and medicine through the power of Generative AI. Our team comprises leading minds and innovators in AI and Biological Science, pushing the boundaries of what is possible. We are dreamers who reimagine a new paradigm for biology and medicine. We are committed to decoding biology holistically and enabling the next generation of life-transforming solutions. As the first mover in pan-modal Large Biological Models (LBM), we are pioneering a new era of biomedicine, with our LBM training leading to ground-breaking advancements and a transformative approach to healthcare. Our exceptionally strong R&D team and leadership in LLM and generative AI position us at the forefront of this revolutionary field. With headquarters in Silicon Valley, California, and a branch office in Paris, we are poised to make a global impact. Join us as we embark on this journey to redefine the future of biology and medicine through the transformative power of Generative AI.
ROLE AND RESPONSIBILITIES
- GPU Cluster Management: Design, deploy, and maintain high-performance GPU clusters, ensuring their stability, reliability, and scalability. Monitor and manage cluster resources to maximize utilization and efficiency
- Distributed/Parallel Training: Implement distributed computing techniques to enable parallel training of large deep learning models across multiple GPUs and nodes. Optimize data distribution and synchronization to achieve faster convergence and reduced training times
- Performance Optimization: Fine-tune GPU clusters and deep learning frameworks to achieve optimal performance for specific workloads. Identify and resolve performance bottlenecks through profiling and system analysis
- Deep Learning Framework Integration: Collaborate with data scientists and machine learning engineers to integrate distributed training capabilities into GenBio AI’s model development and deployment frameworks.
- Scalability and Resource Management: Ensure that the GPU clusters can scale effectively to handle increasing computational demands. Develop resource management strategies to prioritize and allocate computing resources based on project requirements.
- Troubleshooting and Support: Troubleshoot and resolve issues related to GPU clusters, distributed training, and performance anomalies. Provide technical support to users and resolve technical challenges efficiently
- Documentation: Create and maintain documentation related to GPU cluster configuration, distributed training workflows, and best practices to ensure knowledge sharing and seamless onboarding of new team members
BASIC QUALIFICATIONS
- Master’s or Ph.D. degree in computer science, or a related field with a focus on High-Performance Computing, Distributed Systems, or Deep Learning
- 2+ years proven experience in managing GPU clusters, including installation, configuration, and optimization
- Strong expertise in distributed deep learning and parallel training techniques
- Proficiency in popular deep learning frameworks like PyTorch, Megatron-LM, DeepSpeed, etc
- Programming skills in Python and experience with GPU-accelerated libraries (e.g., CUDA, cuDNN)
- Knowledge of performance profiling and optimization tools for HPC and deep learning
- Familiarity with resource management and scheduling systems (e.g., SLURM, Kubernetes)
- Strong background in distributed systems, cloud computing (AWS, GCP), and containerization (Docker, Kubernetes)
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. GenBio AI participates in the U.S. Department of Homeland Security’s E-Verify program to confirm the employment eligibility of all newly hired employees. For more information on E-Verify, please visit www.e-verify.gov. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
How to Get Visa Sponsorship as a Hpc Engineer
Confirm your degree qualifies for STEM OPT
HPC roles almost always require a degree in computer science, electrical engineering, or a related STEM field. Verify your program appears on the official STEM Designated Degree Program list before applying, so you can offer employers a 24-month authorization window.
Target employers with established OPT infrastructure
National laboratories, defense contractors, and research-intensive universities hire HPC engineers regularly and typically have HR teams experienced with OPT and E-Verify compliance. These organizations are less likely to pass on a strong candidate due to authorization uncertainty.
Lead with technical depth, not visa status
HPC hiring managers prioritize parallel computing skills, MPI, OpenMP, and performance profiling experience. Get your technical qualifications in front of them first. Visa status conversations go more smoothly when the employer is already convinced you're the right person for the role.
Know your OPT end date and plan your timeline
HPC positions often involve lengthy hiring processes with technical screens and team interviews. Start your job search at least four months before your OPT expires so authorization deadlines don't pressure you into accepting a role that isn't the right fit.
Highlight projects that demonstrate scale
Employers want evidence you've worked on compute-intensive problems. Quantify your contributions: cluster sizes, speedup ratios, job throughput improvements. Research projects, thesis work, and internships all count. Concrete performance metrics make your resume stand out against candidates without HPC-specific experience.
Understand E-Verify requirements before you start
STEM OPT employers must be enrolled in E-Verify before your extension begins. Confirm this early in the offer stage, not after you've signed. If an employer isn't enrolled, they'll need to complete enrollment before your start date or you cannot legally work.
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Get Access To All JobsFrequently Asked Questions
Do HPC Engineer jobs qualify for the 24-month STEM OPT extension?
Yes, in most cases. HPC engineering roles typically fall under computer science, electrical engineering, or computational science degree programs, most of which appear on the STEM Designated Degree Program list. If your specific program is listed, you're eligible to apply for the 24-month STEM OPT extension through your DSO, giving you up to three years of total OPT work authorization.
What types of employers hire HPC engineers on OPT?
National laboratories such as Argonne, Lawrence Berkeley, and Oak Ridge, along with research universities and defense contractors, are among the most consistent hirers of HPC engineers and have experience navigating OPT authorization. Large tech companies with infrastructure or AI research divisions also hire for these roles. You can browse OPT-friendly HPC Engineer openings directly on Migrate Mate, which filters for employers open to F-1 students.
Can I work on classified HPC projects as an F-1 OPT student?
Generally, no. Most classified projects at national labs and defense contractors require a U.S. security clearance, which F-1 OPT students are not eligible to hold. However, many national laboratories and defense-adjacent employers also run unclassified HPC research programs that are open to international students. Focus your applications on open research divisions or industry teams not tied to classified work.
What technical skills strengthen an HPC Engineer's OPT job application?
Proficiency in MPI, OpenMP, CUDA, or OpenCL is expected for most HPC roles. Experience with job schedulers like Slurm or PBS, performance profiling tools such as VTune or TAU, and familiarity with large-scale storage systems all add significant weight. Employers hiring on OPT want candidates who can contribute immediately, so documented project experience on high-performance clusters is more persuasive than coursework descriptions alone.
How do I handle the OPT authorization gap if my job search takes longer than expected?
F-1 students are allowed up to 90 days of unemployment during standard OPT and up to 150 days during the STEM OPT extension. If your search is running long, prioritize roles at employers already enrolled in E-Verify, since that removes one potential delay from the hiring process. Stay in close contact with your DSO to monitor your unemployment days and explore whether a cap-exempt H-1B or other status change may be appropriate if authorization is close to expiring.
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