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Temporary Research Software Engineer Jobs in California

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Temporary Research Software Engineer information

What is the difference between Temporary Research Software Engineer vs Research Software Engineer?

AspectTemporary Research Software EngineerResearch Software Engineer
CredentialsTypically requires a relevant degree in computer science or related field; often a temporary or contract basisUsually requires a degree in computer science, engineering, or related field; permanent or long-term position
Work EnvironmentContract-based, project-specific, often in academic or research institutionsFull-time, ongoing research teams in academia, industry, or government labs
Employer & Industry UsageUsed by research institutions, universities, and companies for short-term projectsEmployed by research organizations, tech companies, and universities for continuous research efforts

In summary, a Temporary Research Software Engineer is a contract-based role focused on short-term projects, while a Research Software Engineer typically holds a permanent position dedicated to ongoing research activities.

What are the most commonly searched types of Research Software Engineer jobs in California? The most popular types of Research Software Engineer jobs in California are:
What are popular job titles related to Temporary Research Software Engineer jobs in California? For Temporary Research Software Engineer jobs in California, the most frequently searched job titles are:
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Temporary Research Software Engineer jobs near you

Sr. Engineer, Research Software & Modeling Infrastructure

Ayar Labs

San Jose, CA • On-site

$127K - $172K/yr

Full-time

Re-posted 14 days ago

Job description

Job Summary:
Ayar Labs is shattering AI data bottlenecks by moving data at the speed of light. As a Research Software Engineer, you will play a pivotal role in shaping the modeling and simulation backbone behind their silicon photonics optical I/O platform.
Responsibilities:
• Partner with photonics and circuits engineers on their modeling code — review, refactor, and help evolve prototypes into well-tested, versioned, and properly packaged tools that teams across the company can depend on.
• Design and maintain the data schemas and interfaces that describe devices, measurements, model parameters, and simulation results across the modeling stack.
• Build and operate data ingestion, cleaning, and curation pipelines that turn raw measurement and simulation outputs into trusted inputs for link analysis and yield prediction.
• Scale simulation and analysis workloads across HPC and AWS cloud environments, so link studies and statistical sweeps run reliably and reproducibly at product-relevant scale.
• Integrate AI and ML tooling into engineering workflows — both to accelerate the software development lifecycle and to augment the team's modeling and data analysis capabilities.
• Bring modern software engineering practice to the group: testing, documentation, CI/CD, reproducible environments, and code review, applied pragmatically in a research setting.
• Collaborate closely with the Photonic Device Design and Analog/Mixed Signal teams to ensure modeling infrastructure evolves with the product roadmap.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Data Science, Physics, Optics/Photonics, Electrical Engineering, or a related field.
• 2+ years of experience building scientific or engineering software in a research, product, or modeling context.
• Strong Python skills, including hands-on experience with the scientific stack (NumPy, SciPy, pandas, networkx, or similar).
• Experience owning and maintaining a codebase with real users — internal teams, collaborators, or an external community — through multiple release cycles.
• Experience designing data schemas and APIs used by other engineers or scientists.
• Experience running large-scale compute workloads in AWS and/or HPC environments (SLURM or equivalent).
• Comfortable working on Linux/UNIX systems and with modern developer tooling (Git, CI, containers).
• Excellent communication skills and a collaborative working style, with the ability to engage deeply with domain experts across disciplines.
Preferred:
• Master's degree or Ph.D.
• Experience with modern data management architectures (e.g., data lakehouse patterns), metadata standards, and query engines.
• Hands-on experience applying AI tools and agentic workflows to engineering or data pipelines.
• Proficiency in C/C++ or another compiled language used alongside Python in scientific codebases.
• Working knowledge of at least one of: photonic device physics, circuits, signal processing, or statistical analysis.
• Prior work on compact models, SPICE-like simulators, or link/yield statistical modeling.
Company:
Ayar Labs develops optical I/O solutions with co-packaged optical engines for AI and high-performance computing infrastructure. Founded in 2015, the company is headquartered in San Jose, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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