Job Description

We Are:

At Synopsys, we drive the innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence, from self-driving cars to learning machines. We lead in chip design, verification, and IP integration, empowering the creation of high-performance silicon chips and software content. Join us to transform the future through continuous technological innovation.

You Are:

As a Senior Staff AI Engineer focusing on AI Optimization & MLOps, you are a trailblazer in the AI landscape. You possess deep expertise in AI model development and optimization, with a keen interest in reinforcement learning and MLOps. Your ability to design, fine-tune, and deploy scalable, efficient, and continuously improving AI models sets you apart. You thrive in dynamic environments, staying at the forefront of AI technologies and methodologies, ensuring that AI solutions are not only cutting-edge but also production-ready. Your collaborative spirit and excellent communication skills enable you to work seamlessly with cross-functional teams, enhancing AI-powered IT automation solutions. With a strong background in AI frameworks and cloud-based AI services, you are committed to driving innovation and excellence in AI deployments.

What You’ll Be Doing:

• Design, fine-tune, and optimize LLMs, retrieval-augmented generation (RAG), and reinforcement learning models for IT automation.
• Improve model accuracy, latency, and efficiency, ensuring optimal performance for IT service workflows.
• Experiment with cutting-edge AI techniques, including multi-agent architectures, prompt tuning, and continual learning.
• Implement MLOps best practices, ensuring scalable, automated, and reliable model deployment.
• Develop AI monitoring, logging, and observability pipelines to track model performance in production.
• Optimize GPU/TPU utilization and cloud-based AI model serving for efficiency and cost-effectiveness.
• Develop tools to measure model drift, inference latency, and operational efficiency.
• Implement automated retraining pipelines to ensure AI models remain effective over time.
• Work closely with cloud teams to optimize AI model execution across hybrid cloud environments.
• Stay ahead of emerging AI technologies, evaluating new frameworks, techniques, and research for real-world application.
• Collaborate to refine AI system architectures and capabilities, while also ensuring models are effectively embedded into IT automation workflows

The Impact You Will Have:

• Enhance the efficiency and reliability of AI-powered IT automation solutions.
• Drive continuous improvement and innovation in AI model development and deployment.
• Ensure scalable and cost-effective AI model serving in cloud and hybrid environments.
• Improve real-time AI processing with minimal downtime and high performance.
• Optimize AI systems for performance, security, and cost in IT automation applications.
• Contribute to the advancement of Synopsys' AI capabilities and technologies.

What You’ll Need:

• 8+ years of experience in AI/ML engineering, with a focus on model optimization and deployment.
• Strong expertise in AI frameworks (LangGraph, OpenAI, Hugging Face, TensorFlow/PyTorch).
• Experience implementing MLOps pipelines, CI/CD for AI models, and cloud-based AI deployment.
• Deep understanding of AI performance tuning, inference optimization, and cost-efficient deployment.
• Strong programming skills in Python, AI model APIs, and cloud-based AI services.
• Familiarity with IT automation and self-healing systems is a plus.

Who You Are:

• Innovative and forward-thinking, constantly seeking to improve and optimize AI models.
• Collaborative and communicative, working effectively with cross-functional teams.
• Detail-oriented and meticulous, ensuring high standards in AI model performance and deployment.
• Adaptable and resilient, thriving in dynamic and fast-paced environments.
• Passionate about AI and its applications in IT automation and beyond.