Designs and builds software tooling, firmware, and infrastructure supporting semiconductor design, verification, manufacturing, and post-silicon validation. Partners with hardware and EDA teams to improve development cycles, yield, performance, and quality. Responsibilities include developing software in C, C++, and Python; building cloud, grid, or HPC infrastructure; creating data pipelines; automating workflows; debugging complex systems; and mentoring engineers.
Chip Software Engineer – Remote
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: Chip Software Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $80,000–$100,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
We are seeking an experienced Chip Software Engineer to design and build software tooling, firmware, and infrastructure that support semiconductor design, verification, manufacturing, and post-silicon validation. In this role you will partner with hardware engineers and EDA teams to build software that accelerates silicon development cycles and improves yield, performance, and quality. The ideal candidate will combine strong software engineering fundamentals with practical experience working alongside hardware teams in EDA, verification, or post-silicon environments. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.
Required Qualifications
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected]. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: Chip Software Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $80,000–$100,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
We are seeking an experienced Chip Software Engineer to design and build software tooling, firmware, and infrastructure that support semiconductor design, verification, manufacturing, and post-silicon validation. In this role you will partner with hardware engineers and EDA teams to build software that accelerates silicon development cycles and improves yield, performance, and quality. The ideal candidate will combine strong software engineering fundamentals with practical experience working alongside hardware teams in EDA, verification, or post-silicon environments. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
- Six or more years of software engineering experience, with significant time in semiconductor environments.
- Strong programming skills in C, C++, and Python.
- Hands-on experience with EDA, verification, or post-silicon validation workflows.
- Solid understanding of hardware-software interaction at a low level.
- Experience building large-scale compute infrastructure (grid, cloud, HPC).
- Strong scripting and automation skills.
- Experience with data pipelines for design or characterization data.
- Excellent debugging and troubleshooting skills.
- Strong communication and documentation skills.
- Exposure to SystemVerilog or other HDLs.
- Familiarity with UVM-based verification workflows.
- Experience with cloud-based EDA workflows.
- Hands-on experience with ML applied to silicon design.
- Advanced degree in EE or related field.
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected]. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
Similar Jobs
Artificial Intelligence • Machine Learning • Generative AI
Build research infrastructure and tooling that enable AI models to design semiconductor chips. Responsibilities include developing reinforcement learning environments, integrating EDA tools, creating evaluation and model harnesses, improving experiment reliability and observability, debugging infrastructure, and converting successful research experiments into reusable systems and training workflows.
Top Skills:
ContainerizationDistributed SystemsElectronic Design Automation (Eda)Formal VerificationPythonReinforcement LearningRtlSystemverilogVerilog
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
Build and maintain customer-ready Linux distributions, installation images, packages, and release processes for NVIDIA AI-RAN and AI products. Integrate NVIDIA software, drivers, and third-party components into Ubuntu and RHEL. Develop build automation and CI/CD pipelines, configure and validate Linux kernels and BSPs, troubleshoot platform integration issues, and collaborate with enterprise Linux and silicon vendors.
Top Skills:
BspCi/CdDebian Package ManagementGitIso Installation ImagesLinuxLinux KernelNvidia DriversRed Hat Enterprise Linux (Rhel)Rpm Package ManagementSoftware Build SystemsUbuntu
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
Develop and support software tools for chip design and verification, optimize workflows, work collaboratively to create high-performance software.
Top Skills:
C++GoUnix/LinuxVerilog
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
