Principal Applied ML Engineer

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Chips are at the center of today's tech-driven world. But how we design and verify them has not fundamentally changed in decades, while their complexity and specialization have skyrocketed due to increasing performance demands from AI. We are a dynamic, fast-moving team of software developers, ML scientists, and research-minded engineers on a mission to change that.

Operating with the agility of a startup but backed by industry-leading verification technologies, we are part of the System Verification Group (SVG). Our charter is to develop state-of-the-art EDA software and hardware platforms (including Xcelium, Jasper, Palladium, Protium, and Helium) and supercharge them with cutting-edge AI, automation, and advanced data-driven workflows.

About This Role

Cadence Design Systems is the leading provider of design automation tools for electronic and intelligent systems design. The ML / Software Engineer – ChipStack SuperAgent Team will be responsible for designing, implementing, and evaluating AI agents that enhance productivity across the semiconductor design lifecycle. This engineer will contribute to the development of robust agent infrastructure, evaluation systems, and production-grade AI capabilities integrated within Cadence’s electronic design automation (EDA) ecosystem.

The role focuses on building reliable, scalable agentic systems that operate within complex engineering workflows. The ideal candidate combines strong software engineering fundamentals with practical experience in ML systems and agent infrastructure, enabling deployment of high-impact AI solutions in production environments.

In this role, you will be  part of the ChipStack AI Super Agent team and  will operate at the forefront of semiconductor design and AI innovation, utilizing advanced AI tools to architect, design, and validate the next generation of verification methodologies. You will collaborate closely with a highly skilled team of machine learning engineers experienced in training large language models at scale, as well as accomplished software engineers with proven expertise in product development and deployment. You will be working on the world’s first agentic AI platform that autonomously designs and verifies chips with up to 10× productivity gains.

Responsibilities

• Design and implement scalable infrastructure for AI agents operating within Cadence’s ChipStack SuperAgent ecosystem.
• Build robust evaluation frameworks to measure agent performance, reliability, and alignment with engineering workflows.
• Develop data pipelines, retrieval systems, and context-engineering strategies to support consistent and grounded agent behavior.
• Contribute to continuous integration, automated testing, and observability systems to ensure production-quality deployment of AI-enabled systems.
• Optimize system performance across latency, cost, reliability, and scalability dimensions.

Required Qualifications

• BS with a minimum of 7 years of experience OR MS with a minimum of 5 years of experience OR PhD with a minimum of 1 year of experience.
• Strong software engineering fundamentals, including design, refactoring, debugging, and testing of complex distributed systems. Demonstrated experience building production-quality systems.
• Understanding of large language models (LLMs) and practical considerations for deploying them in real-world systems (latency, cost, reliability, monitoring).
• Experience designing evaluation frameworks for AI systems, including benchmarking, regression testing, and failure analysis.

Skills of Interest

• Agent architecture: Experience with reason–act loops, planning/evaluation/self-correction patterns, tool/function calling, persistent memory systems, and structured outputs.
• LLM engineering: Familiarity with frontier LLMs and trade-offs across model families; experience with prompt engineering, context management, and alignment techniques.
• Retrieval and data systems: Understanding of RAG pipelines, embeddings, indexing strategies, chunking methodologies, and grounding techniques. Infrastructure and observability: Experience building logging, tracing, monitoring, and evaluation systems for ML/AI applications.
• AI-assisted development workflows: Leveraging AI tools to enhance engineering productivity and code quality.
• Interest in semiconductor design, EDA workflows, and high-performance computing environments.

Our Culture

• Challenge the status quo: We are innovators who challenge industry norms and push forward our vision of how silicon should be built.
• Strong opinions, loosely held: We are low on ego, but high on collaboration. We are okay to be wrong and are always open to learning.
• Ship fast, ship quality: We ruthlessly prioritize what matters. We build at lightning speed, but never compromise on the high standards required by the semiconductor industry.
• Proud of our craft: Attention to detail is in our DNA. We take pride in what we build and go the extra mile to ensure an exceptional experience for our users.

The annual salary range for California is $136,500 to $253,500. You may also be eligible to receive incentive compensation: bonus, equity, and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the salary range is a guideline and compensation may vary based on factors such as qualifications, skill level, competencies and work location. Our benefits programs include: paid vacation and paid holidays, 401(k) plan with employer match, employee stock purchase plan, a variety of medical, dental and vision plan options, and more.

We’re doing work that matters. Help us solve what others can’t.