Required Qualifications

• BS or MS in Computer Science, Electrical Engineering, or a related field plus 1+ year of full-time industry experience
• Strong programming skills in Python (PyTorch or similar ML frameworks preferred)
• Hands-on experience with machine learning / deep learning projects
• Experience working with messy, real-world data and defining quality metrics
• Demonstrated ability to work across abstraction layers - from research prototypes to production systems
• Demonstrated exposure to hardware design, verification, or EDA workflows through coursework, research, or industry work
• Proven track record of collaboration with with other deeply technical teams

Preferred Qualifications

• Background or exposure to silicon design / EDA workflows (e.g., RTL, verification, specs, UVM, synthesis) and hardware description language, e.g., verilog or systemverilog
• Industry experience with LLMs, agentic systems, or domain-adapted AI systems
• Experience with synthetic or programmatic data generation, simulation-driven data, or otherwise automated dataset construction
• Experience using Databricks or similar large-scale data processing platforms
• Experience collaborating in fast-moving, cross-functional teams

What We Offer

• Work on foundational and unsolved problems at the frontier of AI and hardware
• Real ownership in your work that directly shapes core product capabilities.
• Work with a team of high-caliber collaborators at the intersection of AI, cloud, and semiconductor design.
• A culture of innovation, precision, and impact, where your work directly shapes the future of engineering.
• Competitive compensation package, including equity participation.

Who This Role Is Great For

• Early-career engineers with strong fundamentals and real-world experience
• PhD graduates who want to see research ideas actually ship
• Engineers excited to work across ML, systems, and silicon
• People who like ambiguity and turning vague problems into concrete systems