Machine Learning R&D

Oversees the design and delivery of an internal benchmark suite for LLMs for hardware design for GenAI applications. Oversees the design and delivery of Agentic AI for HW design. Identifies and enables the pursuit of measurably impactful technical ideas and research directions for GenAI applications in HW design. Coaches others to complete tasks and achieve goals. Aligns individual growth with department goals. Manages the project team's capabilities and ambiguity across situations while ensuring deadlines are met. Engages with cross-functional teams to identify technical gaps and opportunities. Defines and continually updates technical project goals and roadmaps. Guides the team's innovation engine from idea to execution. Develops effective working relationships with cross-functional and/or external stakeholders. Communicates effectively with partner teams, providing timely updates on project status and expectations. Stays current on AI, systems, and hardware-software advances relevant to the field of AI for chip design. Exemplifies and encourages respect, dignity, and fairness; contributes to a positive culture. PhD in Computer Science, Electrical Engineering, or a related field. At least 5 years of industry experience in Machine Learning/GenAI and MLOps. Industry experience in ML/AI product development and deployment. Deep knowledge of foundational model architectures and industry experience in foundation model development. Proficiency in programming languages such as Python, Java, or C++. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). Hands-on industry expertise in Agentic AI tools, frameworks, and best practices (e.g. Codex, Claude Code, OpenCode, Langchain, Langchain, Agno). Excellent problem-solving skills and attention to detail. Strong communication skills and ability to work collaboratively in a team environment. Ability to manage multiple highly complex projects while meeting quality expectations and adhering to the company's standards of ethical behavior. Ability to encourage continuous improvement and alternative viewpoints to challenge ingrained practices. Ability to set clear expectations. Ability to provide constructive feedback to encourage skills growth Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. 6+ months of experience developing and/or optimizing machine learning models, systems, platforms, or methods.