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Scientific Software Jobs in California (NOW HIRING)

DD-Scientific Data

Scientific Data Engineer

Bodega Bay, CA · On-site

$135K - $163K/yr

You will develop new methods and software tools that enable scientific knowledge discovery using modern data management and machine learning technologies and advance the state-of-the-art in data ...

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Scientific Software information

See California salary details

$82.4K

$101.2K

$133.7K

How much do scientific software jobs pay per year?

As of Sep 7, 2026, the average yearly pay for scientific software in California is $101,157.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,800.00 and $113,500.00 per year, depending on experience, location, and employer.

What is a scientific software developer?

A scientific software developer is a professional who designs, creates, and maintains software tools and applications used for scientific research and data analysis. These developers work closely with scientists and researchers to translate complex scientific problems into computational solutions. Their work often involves programming, algorithm development, and optimizing code for high-performance computing environments. Scientific software developers play a critical role in fields like physics, biology, chemistry, and engineering by enabling researchers to process and visualize large datasets, simulate experiments, and gain insights from data.

How does a scientific software professional typically collaborate with domain scientists and research teams?

Scientific Software professionals often work closely with domain scientists, researchers, and data analysts to develop and maintain tools that enable scientific discovery. Collaboration usually involves requirements gathering, iterative feedback on prototypes, and integrating scientific algorithms into user-friendly applications. Effective communication skills are crucial, as you’ll be translating complex scientific needs into robust, efficient code and ensuring the software meets both research objectives and usability standards. Team environments tend to be interdisciplinary, offering the opportunity to learn from experts in various scientific fields while contributing your technical expertise.

What are the key skills and qualifications needed to thrive in scientific software roles, and why are they important?

To excel in Scientific Software roles, you need a strong background in computer science, mathematics, or a scientific discipline, along with demonstrated programming proficiency (often in Python, C++, or MATLAB). Familiarity with version control systems (like Git), scientific computing libraries, and sometimes specialized tools (e.g., HPC clusters or cloud platforms) is typically expected. Strong analytical thinking, problem-solving, and effective communication skills help bridge the gap between scientific users and technical implementation. These skills ensure the creation of robust, efficient, and user-friendly software that accelerates scientific research and discovery.

What is the difference between Scientific Software vs Data Analyst?

AspectScientific SoftwareData Analyst
Required CredentialsTypically requires degrees in science, engineering, or computer science; coding skillsUsually requires degrees in statistics, mathematics, or related fields; strong analytical skills
Work EnvironmentResearch labs, scientific institutions, academia, industry R&DBusiness, finance, healthcare, marketing sectors
Employer & Industry UsageUsed by scientists and engineers for simulations, modeling, data analysisUsed by companies for data interpretation, reporting, decision-making

Scientific Software professionals focus on developing and utilizing specialized tools for scientific research and simulations, often working in research environments. Data Analysts interpret data to inform business decisions across various industries. While both roles require analytical skills and familiarity with data, Scientific Software roles emphasize scientific computing and programming, whereas Data Analysts focus on data interpretation and visualization.

What are popular job titles related to Scientific Software jobs in California?

For Scientific Software jobs in California, the most frequently searched job titles are:

What job categories do people searching Scientific Software jobs in California look for?

The top searched job categories for Scientific Software jobs in California are:

Scientific Software jobs near you
Infographic showing various Scientific Software job openings in California as of August 2026, with employment types broken down into 88% Full Time, 10% Part Time, and 2% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $101,157 per year, or $48.6 per hour.

Scientific Software Engineers

Jobs for Humanity

Santa Clara, CA • On-site

Full-time

Re-posted 24 days ago

Key responsibilities

  • Design, build, deploy, and operate cloud-native microservices and APIs for scientific computing workloads on DGX cloud.

  • Design services and take ownership of the underlying cloud infrastructure for physics-informed and data-driven scientific workflows.

  • Design, build, deploy, and operate scalable I/O infrastructure for checkpointing, data loading, and pre/post-processing of data.

Job description

Company Description
Jobs for Humanity is collaborating with Upwardly Global and with Nvidia to build an inclusive and just employment ecosystem. We support individuals coming from all walks of life.
Company Name: Nvidia
Job Description

Senior System Software Engineer - Scientific Computing PaaS
locations: US, CA, Santa Clara; US, Remote
time type: Full time
posted on: Posted Today
job requisition id: JR1979896
We are seeking a Sr System Software Engineer to help us build out our scientific computing platform on Nvidia DGX Cloud. We are building a cloud-based accelerated scientific computing platform as a service on the Nvidia DGX cloud. This DGX scientific computing cloud platform enables Physics-based Numerical Simulation Solvers, AI-based Training, Inference, and Visualization workflow for physical science and engineering problems. Those applications include Weather prediction, Climate modeling, Industrial design, and Digital twins simulation in various domains e.g. Aerospace, Automotive, Sports, Renewable energy, Bio-medical, and many more.
Are you passionate about solving rewarding problems at scale? Do you enjoy crafting robust, critical services for compute and data-intensive workloads? If so, you may be a phenomenal fit for our team!
What you'll be doing:
Design, Build, Deploy, and Operate Cloud-native microservices and APIs for scientific computing workload on DGX cloud.
Design services and take ownership of underlying cloud infrastructure for physics-informed and data-driven scientific workflows.
Design novel algorithms and actively engage with operations to increase overall system performance, it spans across the stack e.g. deep understanding of application code e.g. DL Framework, Numerical Solvers, Microservices, APIs, and Heterogeneous accelerated computing with CPUs and GPUs.
Design, Build, Deploy, and Operate scalable I/O infrastructure for checkpointing, data loading, pre & post-processing of data.
Optimize compute, storage, and network architecture specific to physics & simulation-driven applications.
What we need to see:
- BS/MS degree in Computer Science or related areas or equivalent experience.
- 10+ years experience working on building and operating distributed compute and data-intensive platform as a service on cloud
- Proven skill in a compiled language (Go, Rust, C++ or otherwise).
- Strong foundational knowledge in Cloud Computing e.g. "The Datacenter is a Computer" architecture, cloud security architecture, virtualization - CPU, Memory and IO, Resource pooling and elasticity.
- Proven skills in Distributed Systems & Parallel Processing e.g. System model of distributed computation e.g. topology abstraction, logical time. Synchronization and deadlock detection in distributed systems, Fault Tolerance and Failure Detection, Consensus and Agreement protocols, Parallel algorithms, shared memory and distributed memory architecture, message passing (MPI, NCCL), Cluster scalability and performance.
- Hands-on Debugging skills with Process, Threads, Deadlock and Synchronization, Scheduling, IPC, Memory management, File system, and I/O structure.
- Strong Evidence of Algorithmic Thinking & System Design skills e.g. Recursion, Graph, Tree, Stack, and Queue, Large scale loosely coupled distributed system design and operational experience.
- Be self-motivated, have strong interpersonal skills, and be able to work independently with multiple teams with minimal direction.
Ways to stand out from the crowd:
- Have built, deployed, and operated AI platforms on HPC clusters. Have built, deployed, and operated cloud-native system including distributed storage, scheduling, and orchestration among compute, storage, and network.
- Configuring and troubleshooting hardware, operating systems, kernels, compilers for maximum performance.
- Hands-on debugging skills to optimize performance of compute, networking, and I/O framework. Extensively worked on third-party source code for debugging and customization.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!
The base salary range is 180,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. You will also be eligible for equity and benefits.
NVIDIA accepts applications on an ongoing basis. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
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