Job Title
Staff Silicon Engineer
About Cognichip
- At Cognichip, we are building AI-native tools that transform how semiconductor engineers create, verify, and optimize chips.
- Our platform combines large proprietary models, agentic workflows, domain-specific engineering intelligence, and high-performance simulation infrastructure to accelerate one of the world's most complex engineering disciplines.
About The Role
- We are seeking a Staff Silicon Engineer who can combine strong software engineering, applied AI/ML, and semiconductor-domain understanding to build production-grade tools for chip design and verification.
- In this role, you will help turn advanced research ideas into practical workflows used by engineers designing real silicon.
- This work matters because chip design is becoming too complex for traditional workflows alone, and AI-native engineering systems can meaningfully change the speed, quality, and scale of semiconductor development.
Key Responsibilities
- Bridge Hardware and Software: Translate deep semiconductor domain expertise into robust software requirements and implementations.
- Develop Agentic Data Pipelines: Architect and implement agentic workflows specifically designed to generate synthetic or augmented RTL and UVM code, creating essential datasets for training and fine-tuning advanced AI models.
- Agentic Workflow Optimization: Fine-tune and optimize agentic workflow for domain-specific engineering tasks such as RTL generation, verification planning, and bug triage.
- Infrastructure Development: Build and maintain high-performance simulation and testing infrastructure to validate AI-generated hardware designs.
- Technical Leadership: Provide mentorship to junior engineers and lead cross-functional projects involving AI researchers and hardware architects.
Required Qualifications
- Experience: 8+ years of experience in silicon design, verification, or hardware-focused software development.
- Semiconductor Domain: Deep understanding of the ASIC/FPGA design lifecycle in at least two of the three phases: RTL design (Verilog/SystemVerilog), UVM-based verification, and physical design flows.
- EDA Tools: Experience with, and being a power user of, commercial EDA tools from major vendors (Cadence, Synopsys, Mentor/Siemens).
- Software Proficiency: Strong programming skills in Python, C++, or similar languages, with experience in building scalable software systems.
- AI/ML Knowledge: Practical experience with LLMs, prompt engineering, or machine learning frameworks (PyTorch/TensorFlow) applied to technical domains.
- Education: MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
Preferred Qualifications
- Experience with LangSmith and LangGraph to build Agentic workflow..
- Background in computer architecture, specifically for AI accelerators or high-performance computing.
- Contributions to open-source hardware or AI projects.
What It's Like Here
- We’re a fast-moving AI startup with a collaborative, high-trust culture.
- We value technical excellence, ownership, and the freedom to experiment.
- Our best work happens when our builders and innovators work closely together to turn ambitious ideas into category defining products.
- We operate on a hybrid schedule with four days in office, one day remote.
- If you’re excited to build cutting edge tools that empower semiconductor engineers and reshape how chips are designed, you’ll feel right at home.