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Internship High Performance Computing Engineer Jobs in Oregon

Cellanome

Machine Learning Engineer

Foster, OR · On-site +1

$160K - $215K/yr

Optimize algorithms for deployment on edge devices, GPUs, and high-performance computing ... Strong programming skills in Python with experience developing production-quality, maintainable ...

Meta

OR

$193K/yr

... or high-performance computing network environments Preferred Qualifications: * Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current ...

New

Arka Infotech Inc

OR

... High Performance Computing, Data Mining and Analysis, Information Life Cycle Management, Map Reduce Programming and Intelligence, Pearl, PHP, Java, C++, Rendering, MapReduce, Scientific Computational ...

Nvidia

OR · On-site

We're looking for a Principal Engineer to join our CSP Engagements team as the technical focal ... High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex ...

Nvidia

OR · On-site

$139K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Design and develop new compiler passes and optimizations required to meet the high-performance and ...

Intel

Senior AI Algorithm Engineer in oneDNN

Hillsboro, OR · On-site +1

$195K - $275K/yr

... High-performance computing (HPC) applications development * 1 year+ Machine learning and deep ... Parallel programming (OpenMP, TBB, or MPI) Job Type:Experienced Hire Shift:Shift 1 (United States ...

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All JobsHigh Performance Computing Engineer JobsInternship High Performance Computing Engineer JobsInternship High Performance Computing Engineer Jobs in Oregon

Internship High Performance Computing Engineer information

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

To thrive as an Internship High Performance Computing Engineer, you need a solid background in computer science fundamentals, programming (especially in C/C++ or Python), and a familiarity with parallel computing concepts, often supported by coursework or relevant project experience. Experience with Linux environments, HPC clusters, and distributed computing frameworks, as well as tools like MPI, OpenMP, or Slurm, is commonly required. Strong problem-solving skills, attention to detail, and the ability to collaborate effectively within technical teams help interns stand out. These skills ensure you can efficiently support computational research, resolve technical challenges, and contribute meaningfully to HPC projects.

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

AspectInternship High Performance Computing EngineerInternship Data Scientist
Required SkillsProgramming (C++, Python), parallel computing, HPC systemsStatistics, machine learning, data analysis, Python/R
Work EnvironmentResearch labs, tech companies, academia with focus on HPC systemsTech firms, finance, healthcare, research institutions
Industry UsageHigh-performance computing projects, scientific simulationsData analysis, predictive modeling, business insights

Internship High Performance Computing Engineers focus on developing and optimizing computational systems for large-scale scientific and engineering problems, requiring skills in parallel programming and HPC environments. In contrast, Internship Data Scientists analyze data to extract insights, using statistical and machine learning techniques. Both roles are valuable in tech and research sectors but differ in technical focus and daily tasks.

What is an Internship High Performance Computing Engineer?

An Internship High Performance Computing (HPC) Engineer is a student or early-career professional who works with advanced computing systems designed for processing large data sets and complex calculations at high speeds. During the internship, they assist in developing, optimizing, and maintaining HPC infrastructure, software, or applications used in scientific research, engineering, or data analysis. The role often involves learning about parallel computing, cluster management, and performance tuning, while gaining hands-on experience with cutting-edge technologies. Interns work under the supervision of experienced HPC engineers, contributing to projects that advance computational capabilities in various fields.

What types of projects can I expect to work on as an Internship High Performance Computing Engineer?

As an Internship High Performance Computing (HPC) Engineer, you will typically contribute to projects involving optimization of scientific applications, performance analysis, and cluster management. Interns often assist with benchmarking software, troubleshooting issues in parallel computing environments, and supporting researchers with technical solutions. You'll likely collaborate closely with senior HPC engineers, system administrators, and academic researchers to ensure efficient use of computing resources. This hands-on experience provides valuable insight into real-world challenges faced in HPC environments and helps build a strong foundation for future roles in the field.
What are popular job titles related to Internship High Performance Computing Engineer jobs in Oregon? For Internship High Performance Computing Engineer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Internship High Performance Computing Engineer jobs in Oregon look for? The top searched job categories for Internship High Performance Computing Engineer jobs in Oregon are:
What cities in Oregon are hiring for Internship High Performance Computing Engineer jobs? Cities in Oregon with the most Internship High Performance Computing Engineer job openings:
Internship High Performance Computing Engineer jobs near you
Infographic showing various Internship High Performance Computing Engineer job openings in Oregon as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Machine Learning Engineer

Machine Learning Engineer

Cellanome

Foster, OR • On-site, Remote

$160K - $215K/yr

Other

Re-posted 13 days ago

Job description

The Machine Learning Engineer will work in close collaboration with the core instrument, assay and software teams to develop algorithms for data analysis and workflow automation. This role reports to the Sr. Director AI and can be based in our San Diego CA or Foster City CA offices. Possibility for Remote.

Key Responsibilities:

  • Design, develop, and optimize advanced algorithms for workflow automation, which include computer vision and computational geometry components.
  • Develop signal-processing and image-analysis algorithms using classical methods as well as modern AI/ML approaches, including neural networks.
  • Perform system-level analysis, simulation, and validation to ensure algorithm performance meets product requirements.
  • Collaborate with cross-functional hardware, software, and product engineering teams to integrate algorithms into our broader software ecosystem.
  • Optimize algorithms for deployment on edge devices, GPUs, and high-performance computing environments with considerations for latency, throughput, and memory efficiency.
  • Create technical documentation, validation reports, and performance metrics to support product development and cross-team collaboration.

Role Requirements:

  • Typically requires a Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field with 5+ years of relevant experience, or a Master's degree with 3+ years of relevant experience.
  • Experience developing, implementing, and validating algorithms for optimization, automation, sensing, data analysis, or image-processing applications.
  • Strong programming skills in Python with experience developing production-quality, maintainable, and well-documented code.
  • Solid understanding of software development fundamentals, including debugging, version control, testing, and code optimization.
  • Familiarity with AI/ML concepts and workflows, including data preprocessing, model training, evaluation, and deployment.
  • Experience with image analysis, computer vision, signal processing, or data-driven algorithm development.
  • Understanding of mathematical foundations relevant to algorithm development, including linear algebra, probability/statistics, optimization methods, and estimation theory.
  • Experience applying algorithmic techniques such as optimization, dynamic programming, numerical methods, or statistical modeling to solve engineering problems.
  • Familiarity with workflow automation, process optimization, or development of efficient data-processing pipelines.
  • Ability to analyze complex technical problems, evaluate tradeoffs, and develop scalable algorithmic solutions.
  • Excellent communication skills and ability to work independently and collaboratively in a multidisciplinary team environment.

Preferred Qualifications:

  • Proficiency in C++, C#, or other high-performance programming languages for algorithm deployment and system integration.
  • Experience developing AI/ML algorithms for image analysis, pattern recognition, anomaly detection, or automated decision systems.
  • Advanced familiarity with modern computer vision and deep learning architectures, including Vision Transformers (ViTs), CNNs, object detection, segmentation, or multimodal AI models.
  • Experience with machine learning frameworks such as PyTorch, TensorFlow, or similar platforms.
  • Experience optimizing algorithms for performance, scalability, memory efficiency, or real-time execution.
  • Familiarity with optimization and estimation techniques such as convex optimization, Kalman filtering, Bayesian estimation, nonlinear optimization, or stochastic methods.

We  provide competitive total compensation packages, including base pay, benefits, and equity. In California, the estimated base salary range for this position is $160,000 - $215,000/year. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

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