Senior Staff Design Automation Engineer
GroqSalary not specified
- Full Time
- Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Semiconductors, Hardware DesignIndustries
Requirements
Candidates should possess a Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related field, along with a minimum of 5 years of experience in RTL design for both ASIC and FPGA technologies. Applicants should have at least 3 years of direct experience working with complex FPGA designs and hardware emulation systems, demonstrating a proven ability to develop and maintain high-quality design documents. Strong verbal and written communication skills are also required.
Responsibilities
The Staff Emulation & FPGA Prototyping Engineer will develop and deploy FPGA-based prototypes for functional and performance validation of SoC subsystems, partition, synthesize, and implement RTL designs on FPGA platforms, ensuring timing closure and optimal resource utilization, and debug FPGA implementations to align with design specifications. They will configure and operate hardware emulation systems such as Synopsys ZeBu, Cadence Palladium/Protium, or Mentor Veloce for large-scale pre-silicon validation, develop and optimize transactors, bridges, and test environments for emulation platforms, identify and root-cause hardware, firmware, and software integration issues, and collaborate with firmware and software teams to enable early bring-up and pre-tapeout driver development. Additionally, the engineer will be responsible for occasional travel to the downtown Toronto office.
Skills
RTL design
FPGA
hardware emulation
design documentation
timing closure
resource utilization
debugging
transactors
bridges
test environments
system-on-chip (SoC)
Untether AI
Enhances AI inference with at-memory computing
About Untether AI
Untether AI enhances the speed and efficiency of AI inference workloads using at-memory computing. This method places the compute element next to memory cells, which boosts compute density and accelerates AI inference for various neural networks, such as those used in vision, natural language processing, and recommendation systems. The company targets businesses that rely on AI technologies and need high-performance computing for inference tasks. Their products, including the runAI200® devices and tsunAImi® accelerator cards, are designed to deliver exceptional performance, with the tsunAImi® card offering over 2 PetaOps. This allows businesses to optimize their AI workloads while maintaining a compact PCI-Express form factor. Untether AI's goal is to provide efficient and cost-effective solutions for companies looking to enhance their AI applications.
Key Metrics
Toronto, CanadaHeadquarters
2018Year Founded
$144.6MTotal Funding
SERIES_BCompany Stage
Hardware, AI & Machine LearningIndustries
51-200Employees