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Scientific Applications Software Engineer Jobs (NOW HIRING)

Net Orbit

Software Engineer

Tempe, AZ · On-site

Net Orbit Inc has openings for the position Software Engineer with Master's degree Computer Science ... Develop, create and modify general computer applications software or specialized utility programs.

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Scientific Applications Software Engineer information

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$110.7K

$152K

How much do scientific applications software engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for scientific applications software engineer in the United States is $110,698.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $135,000.00 per year, depending on experience, location, and employer.

What is a scientific applications software engineer?

A Scientific Applications Software Engineer is a professional who designs, develops, and maintains software applications used for scientific research and analysis. They work closely with scientists and researchers to understand their computational needs and create tools that enable data analysis, simulation, and visualization. Their work often involves programming in languages like Python, C++, or MATLAB, and integrating software with laboratory instruments or high-performance computing systems. This role requires both strong programming skills and a good understanding of scientific concepts relevant to their field.

What are the key skills and qualifications needed to thrive as a scientific applications software engineer?

To thrive as a Scientific Applications Software Engineer, you need strong programming abilities (often in Python, C++, or Java), a solid background in mathematics or science, and typically a degree in computer science, engineering, or a related field. Familiarity with scientific computing libraries (like NumPy, SciPy), high-performance computing systems, and version control tools is essential, and certifications in relevant programming languages or platforms are beneficial. Analytical thinking, problem-solving, and effective collaboration with researchers are crucial soft skills for success in this role. These skills ensure the efficient development, optimization, and support of specialized software that advances scientific research.

What are some common challenges scientific applications software engineers face when developing software for research environments?

Scientific Applications Software Engineers often encounter challenges related to integrating complex scientific algorithms with user-friendly software interfaces. They must ensure that the applications are both computationally efficient and adaptable to evolving research needs, which may require frequent collaboration with scientists to clarify requirements. Additionally, maintaining code quality and reproducibility in rapidly changing research projects can be demanding, as the software must be robust enough to support rigorous scientific analysis while accommodating new data types and methods.

What is the difference between Scientific Applications Software Engineer vs Data Scientist?

AspectScientific Applications Software EngineerData Scientist
Required CredentialsBachelor's or Master's in Computer Science, Engineering, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, scientific institutions, tech companiesBusiness, tech companies, research organizations
Industry UsageDevelops scientific software, simulations, data analysis toolsAnalyzes large datasets, builds predictive models, data visualization

While both roles involve data analysis and programming, Scientific Applications Software Engineers focus on developing software for scientific research and simulations, whereas Data Scientists primarily analyze data to extract insights and build models. The roles often overlap in skills but differ in their core objectives and application areas.

What are popular job titles related to Scientific Applications Software Engineer jobs?

For Scientific Applications Software Engineer jobs, the most frequently searched job titles are:

Infographic showing various Scientific Applications Software Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 79% Full Time, 15% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $110,698 per year, or $53.2 per hour.

Physics Applications - Software Engineer

Palo Alto, CA • On-site

Vinci AI
See more jobs at Vinci AIexternal

$210K - $285K/yr

Full-time

Re-posted 6 hours ago

Key responsibilities

  • Define and implement high-quality, reusable software libraries for the core simulation engine.

  • Drive code quality, testability, and architectural standards across the team to ensure scalability and maintainability.

  • Take ownership of critical system components, mentor junior engineers, and collaborate with physicists, AI researchers, and other experts.

Job description

The Mission
At Vinci, we are building the operator intelligence infrastructure that modern hardware programs rely on daily. We have already proven that a single foundation model works out of the box across physics on realistic production workloads.
  • Trained on PetaBytes of structured physics data
  • Running billion-voxel inference in production
  • Tier-1 semiconductor and hardware customers
  • Operating across multiple physical scales and operator regimes

We are scaling deployment at industrial magnitude:
  • Increase simulation throughput by two orders of magnitude
  • Expand simulation capabilities to maximize utility and domain coverage
  • Support global, multi-entity deployment across Tier-1 ecosystems

Our ambition is to become the default operator intelligence layer that hardware companies run on.
Solving Across Space and Time
Our proven unified model architecture allows users to rapidly obtain steady state solutions of various partial differential equations. We are expanding this capability to support new physics, new geometries. Beyond that we are building out transient solutions, modeling interactions, deformation and dynamics. A core challenge as we scale out support is designing simple and clean interfaces that turn portions of the codebase into a clean library, ensuring they are correct and accurately reflect the underlying physics being modeled. These are promising applications where Vinci's approach can not only reduce the compute load but also achieve greater accuracy.
What You Will Do
Your north star will be production and delivering value to our customers while establishing and maintaining the technical integrity of our codebase.
In this role you will define and implement high-quality, reusable software libraries for our core simulation engine. You will drive code quality, testability, and architectural standards across the team, ensuring our production system scales gracefully and remains maintainable. This includes designing interfaces that are easy to access and correctly reflect the physics they are modeling. You will take ownership of critical system components, mentor junior engineers, and guide the team in transforming research prototypes into hardened, customer-facing features.
You will work with Physicists, AI researchers, Software Engineers and Computational Geometry experts. You will collaborate closely with this team to enforce software engineering best practices throughout the full development lifecycle, from ideation to deployment.
What We're Looking For
Qualifications:
  • 8+ years of experience in high-quality software development, with significant experience designing and building production-grade systems.
  • Prior experience with scientific computing or physics simulators (FEM, FEA, Molecular Dynamics, FDTD), or large-scale machine learning systems.
    • STEM MSc, PhD preferred but not required.
  • Demonstrated ability to lead technical initiatives focused on code health, modularity, and system correctness.
  • Expertise in building robust, tested, and maintainable software libraries and APIs.
  • Strong proficiency in modern software development practices, including system design, agentic coding, testing frameworks, and continuous integration/delivery (CI/CD).
  • Have contributed to a production data processing system.

We are very excited to talk with you if you have
  • Experience building and maintaining core ML, data infrastructure, or numerical computing software (e.g., PyTorch, Numpy, Cuda, distributed systems).
  • Experience going from early stage prototype moving to a production environment
    • At a Startup or National Lab
  • Have leveraged simulation for design or data generation purposes.

Engineering Expectations
  • Architectural Leadership: Define and uphold rigorous software design standards to ensure the code base remains clean, modular, and scalable in a production environment.
  • Code Health and Testability: Drive strong CI, comprehensive regression testing, and validation discipline across all components.
  • Technical Ownership: Capable of independently solving complex architectural problems and taking ownership of core model infrastructure evolution.
  • Mentorship: Mentor scientists & engineers on best practices, performance optimization, and system design.

Why Vinci
Join a rare early-stage startup that has successfully moved a foundational product from research to real-world, production environments, already serving Tier-1 semiconductor and hardware customers.
Our Mission & Impact
Vinci is building the operator intelligence infrastructure that modern hardware programs rely on daily. We are scaling our solution to accelerate design validation from hours to seconds. You will contribute to expanding our unified model architecture, which currently runs billion-voxel inference, into the transient domain-a key frontier in modeling interactions, deformation, and dynamics. Our ambition is to become the default operator intelligence layer for hardware companies.
Growth & Opportunity
This is a unique opportunity for technical and professional growth, as you will define a foundational abstraction layer early in the company's trajectory. The team is small, friendly, and accessible. You will be empowered to "own and architect large pieces of the system" alongside a team of Physicists, AI researchers, Software Engineers, and Computational Geometry experts. This includes greenfield opportunities to expand Vinci's core capabilities.
Leadership
You will work with spectacular technical leaders like CTO Sarah Osentoski and CEO Hardik Kabaria, whose vision is to greatly accelerate physics simulations with ML while retaining solver grade accuracy.

Apply