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Entry Level High Performance Computing Engineer Jobs in Berkeley, CA

Junior System Engineer

Fremont, CA · On-site

$80K - $95K/yr

... of high-performance computing systems and server platforms. The ideal candidate has strong ... Collaborate with engineering teams to define system specifications and evaluate the interface ...

About the Role As a Supercomputing Engineer at Periodic Labs, you will design, build, and operate the high-performance computing infrastructure that powers our AI and scientific research. Our models ...

... High Performance Computing, HPC, Distributed Systems, CUDA, PyTorch, JAX, TensorFlow, Neural Networks, Transformer Models, Retrieval Augmented Generation, RAG, Synthetic Data, Data Engineering, Data ...

... High Performance Computing, HPC, Distributed Systems, CUDA, PyTorch, JAX, TensorFlow, Neural Networks, Transformer Models, Retrieval Augmented Generation, RAG, Synthetic Data, Data Engineering, Data ...

... High Performance Computing, HPC, Distributed Systems, CUDA, PyTorch, JAX, TensorFlow, Neural Networks, Transformer Models, Retrieval Augmented Generation, RAG, Synthetic Data, Data Engineering, Data ...

... High Performance Computing, HPC, Distributed Systems, CUDA, PyTorch, JAX, TensorFlow, Neural Networks, Transformer Models, Retrieval Augmented Generation, RAG, Synthetic Data, Data Engineering, Data ...

... High Performance Computing, HPC, Distributed Systems, CUDA, PyTorch, JAX, TensorFlow, Neural Networks, Transformer Models, Retrieval Augmented Generation, RAG, Synthetic Data, Data Engineering, Data ...

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Entry Level High Performance Computing Engineer information

See Berkeley, CA salary details

$36.7K

$84.9K

$144.5K

How much do entry level high performance computing engineer jobs pay per year?

As of Jun 21, 2026, the average yearly pay for entry level high performance computing engineer in Berkeley, CA is $84,930.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,100.00 and $96,100.00 per year, depending on experience, location, and employer.

What is the average salary for an HPC engineer in the US?

The average salary for an entry-level high performance computing (HPC) engineer in the US typically ranges from $70,000 to $90,000 annually, depending on experience, location, and specific technical skills such as parallel programming and cluster management. Salaries tend to increase with expertise in areas like GPU computing, Linux systems, and performance optimization.

What is an Entry Level High Performance Computing Engineer?

An Entry Level High Performance Computing (HPC) Engineer is a professional who assists in designing, building, and maintaining high-speed computing systems used for complex computations and large-scale data analysis. They typically work with supercomputers or computer clusters in fields like scientific research, finance, or engineering. Responsibilities often include configuring hardware, optimizing software, and troubleshooting system issues, usually under the guidance of more experienced engineers. Entry-level engineers may also help monitor system performance and support users in running high-performance applications.

What engineers make $500,000?

High-level engineers in specialized fields such as software engineering, data engineering, or systems engineering can reach salaries of $500,000 or more, especially with extensive experience, advanced skills, and leadership roles. These roles often require expertise in high-demand technologies, certifications, and working in competitive industries or companies with lucrative compensation packages.

What engineers make $300,000 a year?

High-performance computing engineers with extensive experience, advanced skills in parallel programming, and expertise in hardware and software optimization can reach annual salaries of $300,000 or more, especially in senior or specialized roles. Such compensation often reflects leadership responsibilities, advanced certifications, or working in high-demand industries like technology or finance.

Can computer engineers make $500,000?

Entry-level high performance computing engineers typically do not earn $500,000 annually; such salaries are usually associated with senior roles, specialized skills, or leadership positions in the field. High salaries in this area often require extensive experience, advanced certifications, or working in high-demand industries or companies. Most entry-level positions start with lower compensation, but salaries can increase significantly with experience and expertise in areas like parallel computing, GPU programming, or data center management.

What are some common challenges faced by entry level High Performance Computing (HPC) engineers, and how can new hires successfully navigate them?

Entry level HPC engineers often encounter challenges such as working with complex parallel computing architectures, optimizing code for performance, and troubleshooting across large-scale, distributed systems. New hires may also need to quickly learn job-specific tools and adapt to rapidly evolving hardware and software environments. To navigate these challenges, it’s important to proactively seek mentorship, participate in team code reviews, and continuously build your skills through hands-on experience and training opportunities. Open communication and collaboration with experienced team members also play a key role in overcoming technical hurdles and growing within the HPC field.

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

AspectEntry Level High Performance Computing EngineerEntry Level Data Scientist
Required CredentialsBachelor's in Computer Science, Engineering, or related field; knowledge of parallel computingBachelor's in Data Science, Statistics, or related; programming skills in Python/R
Work EnvironmentResearch labs, tech companies, supercomputing centersBusiness, tech firms, research institutions
Industry UsageHigh-performance computing, scientific research, simulationsData analysis, machine learning, predictive modeling

Entry Level High Performance Computing Engineers focus on developing and optimizing computational systems for scientific and technical applications, while Entry Level Data Scientists analyze data to extract insights. Both roles require programming skills and a strong technical background, but they serve different industry needs and environments.

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

To thrive as an Entry Level High Performance Computing Engineer, you typically need a solid background in computer science or engineering, familiarity with parallel computing concepts, and proficiency in programming languages like C/C++ or Python. Experience with Linux environments, HPC cluster management tools, and knowledge of batch schedulers or MPI/OpenMP are often required. Strong problem-solving abilities, teamwork, and effective communication help you excel in collaborating with researchers and technical teams. These skills ensure efficient support and optimization of complex computing systems critical for scientific and technical advancements.
What are popular job titles related to Entry Level High Performance Computing Engineer jobs in Berkeley, CA? For Entry Level High Performance Computing Engineer jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Entry Level High Performance Computing Engineer jobs in Berkeley, CA look for? The top searched job categories for Entry Level High Performance Computing Engineer jobs in Berkeley, CA are:
Infographic showing various Entry Level High Performance Computing Engineer job openings in Berkeley, CA as of June 2026, with employment types broken down into 1% As Needed, 92% Full Time, 6% Part Time, and 1% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $84,930 per year, or $40.8 per hour.
High Performance Computing Software Engineer

High Performance Computing Software Engineer

Zendar

Berkeley, CA • On-site

$140K - $200K/yr

Full-time

Posted 12 days ago


Job description

About Zendar:

Zendar is building perception for physical AIgiving engineers a strong foundation for creating world-class robotics applications. At Zendar, you'll work on perception foundation models that enable robots to understand and interact with their environments across a wide range of industries.
Zendar pioneered RF perception that delivers a vision-like, semantically segmented understanding of the environmentrunning on embedded automotive systems using only radar data. This RF perception forms the backbone of Zendar's next-generation foundation models, which are built around early fusion of RF and vision data.
This architecture inverts the traditional perception stack. Instead of treating RF signals as secondary, Zendar's models combine vision's high angular resolution with RF's strong temporal and spatial understanding at the earliest stages of perception. The result is a system that sees farther, remains robust to occlusion and adverse weather, and operates far more efficiently than vision-only or lidar-based approaches.

See a demo of Zendar's foundational RF perception
At Zendar, you'll work at the cutting edge of autonomous mobility and roboticsadvancing foundation models that will power the next generation of physical AI systems. You'll work with large-scale, real-world, multi-modal datasets composed of synchronized and calibrated radar, camera, and lidar data collected across multiple continents.
Our team brings together deep expertise across hardware, signal processing, machine learning, and software engineering, with decades of experience in sensing and perception. We are a global team with offices in Berkeley, Lindau (Germany), and Paris (France). Zendar is well-funded by leading Tier-1 venture capital firms and has established strong industry partnerships.
Although AI is central to what we build, our hiring process is intentionally human: every rsum is reviewed by a real person.

Your Role:

Zendar's Semantic Spectrum perception technology extracts a rich scene understanding from radar sensing, augmented by additional sensors such as IMU and cameras. In addition, Zendar is building an actuation stack on top of its perception outputs. All of these capabilities must run reliably, efficiently, and with deterministic timing on ruggedized embedded platforms suitable for field deployment in the field.

We are seeking experienced software engineers to implement and optimize a high-performance pipeline capable of handling these intensive workloads, leveraging the accelerators available in modern heterogeneous embedded computing platforms. This position is ideal for engineers who are passionate about pushing the limits of modern computer hardware to achieve higher performance, and who are interested in bridging the gap between machine learning research and deployment of AI models on the edge.

It is an exciting opportunity to tackle real-world challenges in bringing algorithms developed in the lab to vehicles operating in diverse physical environments.

What you'll do:

In this role, you will work closely with our researchers to explore the trade-offs between algorithm output quality and its compute efficiency, while creating performance optimized embedded implementations runnable on our production hardware. You will also collaborate with product teams to tackle performance issues encountered in the deployment of our software. To have a thorough understanding of the heterogeneous computing platform we target, you are expected to devise methodologies and microbenchmarks to exercise relevant processing blocks in the system. The knowledge acquired would be incorporated into the evolution of our software system architecture.

What We Look For:

  • Proficiency with modern C++ (we use C++ 17) and python
  • Experience programming multiprocess/multithreaded applications in production environment
  • Experience profiling and analyzing the performance of C++/python applications
  • Experience in optimizing performance for compute intensive workloads on modern computer systems
  • Experience developing for embedded Linux or POSIX systems
  • Familiarity with professional software development tools, such as source control (git), unit testing, and profiling
  • Strong communication and cross-functional collaboration skills

Bonus Points:

  • Experience with developing mission critical software (e.g. aviation or autonomous vehicles)
  • Experience developing software that runs on an RTOS
  • Experience with radar, lidar, cameras, GPS/IMU, or other automotive sensors
  • Experience mentoring team members on software development and best practices
  • Familiarity with CUDA/OpenCL
  • Experience deploying machine learning models in embedded systems

What We Have To Offer:

  • Opportunity to make an impact at a young, venture-backed company in an emerging market
  • Competitive salary from $140-200k depending on experience, benefits and equity
  • Daily catered lunch and a stocked fridge (when working out of the Berkeley, CA office)

Zendar is an equal opportunity employer.

Zendar participates in E-Verify.


Zendar logo

About Zendar

Sourced by ZipRecruiter

Industry

Software development

Company size

11 - 50 Employees

Headquarters location

Berkeley, CA, US

Year founded

2017