Bronco AI
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About
Bronco is an applied AI lab focused on accelerating chip development. They provide AI tools to augment and accelerate design verification (DV) for chip teams. Bronco's technology is deployed in industry, catching bugs and providing velocity advantages. They are backed by investors including 8VC, Elad Gil, SV Angel, YC, and Contrary. Bronco aims to close the verification gap as chips become more specialized and timelines shrink. Their AI accelerates mundane DV workflows, reducing hours to minutes or minutes to seconds.
Platform
Features
• accelerating dv workflows
• clearing backlogs
• bug catching
• ai-driven design verification
Job Opportunities
Founding ML Research Engineer
Bronco AI accelerates chip development using AI-powered tools for design verification, catching bugs and speeding up workflows.
Benefits:
Competitive salary and equity package
Comprehensive benefits including health, vision, and dental coverage
High-ownership, high-velocity environment with rapid learning opportunities
Chance to work on a profound technical problem that, if solved, will accelerate the future of technology development and civilization
Education Requirements:
A Bachelor's degree in Computer Science, Software Engineering, or related field; advanced degree preferred
Experience Requirements:
You are an exceptional researcher who has designed large-scale ML systems
Experience building LLM applications and agentic LLM systems
Familiarity with cloud computing platforms and distributed systems
Have strong intuition about computer architecture to quickly understand chip design and verification tasks
Strong communication abilities and experience working in cross-functional teams
Other Requirements:
Strong proficiency in Python and AI/ML frameworks like PyTorch
Responsibilities:
Design and implement core components of our AI-powered engineering systems
Integrate classical algorithms and deep learning-based approaches across modalities
Utilize our GPU clusters for efficient training, finetuning, and inference of AI models, ensuring optimal performance and scalability.
Explore and implement efficient inference techniques to reduce computational costs and improve the speed of model predictions without compromising quality.
Stay ahead of the curve in AI research, particularly in the areas of LLMs, to continually improve our technologies and methodologies.
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