About Us

Bronco is an applied AI lab helping chipmakers keep Moore’s law going. Our mission is to build AI silicon verification agents that find bugs, drive coverage, and help companies ship working chips on time.

We're currently deployed alongside verification teams at leading chip companies building next generation hardware (4 nm process node).

We are well-funded and backed by tier-1 investors, including YC, 8VC, Elad Gil, SV Angel, and Contrary Capital. We have also established strong relationships with the leading academic and industry researchers in the field of AI for chip design. Our advisors have won multiple Best Paper Awards at leading conferences, been cited tens of thousands of times, and received some of the highest honors in the microelectronics and EDA industries.

About the role

As a founding ML research engineer at Bronco AI, you will be building world-class intelligent reasoning systems for chip verification. You’ll push model capabilities across modalities to develop AI systems that can plan, reason, and debug like the best human verification engineers. The ideal candidate is an experienced ML researcher/engineer with previous exposure to chip development programs who seeks to get closer to the cutting edge of AI and work in a high-ownership, high-velocity environment. 

Who you are

• You instinctively tinker. Your first thought when a paper comes out is to find the source code and try running it. You bias towards experimentation and always have something new to try. 
• You scoff at the impossible. You fear local minima. You challenge existing best practices and are willing to rethink things from the ground up.
• You learn incredibly quickly. You’re an expert in multiple technical domains and you want to become an expert in a few more. You feel confident jumping headfirst into deep technical challenges, learning on the fly, and delivering results.

What you'll do

• 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.
• Collaborate with domain experts to incorporate specialized knowledge into AI systems

We'd like to see

• You are an exceptional researcher who has designed large-scale ML systems
• A Bachelor's degree in Computer Science, Software Engineering, or related field; advanced degree preferred
• Strong proficiency in Python and AI/ML frameworks like PyTorch
• 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

We’d prefer if you had

• A background or experience with Electrical or Computer Engineering
• Familiarity with chip design and verification processes
• Experience with EDA tools (Synopsys, Vivado, etc.) 
• Publications at leading ML (NeurIPS, ICLR, ICML, etc.) or EDA (DAC, ICCAD, DVCon, etc.) conferences

What We Offer

• 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

If you're passionate about revolutionizing chip verification through AI and ready to make a significant impact in a well-funded startup environment, we want to hear from you!