ai engineer

Synopsys drives innovations that shape the way people live and connect, focusing on technology central to the Era of Pervasive Intelligence, ranging from self-driving cars to learning machines. The company transforms the future through continuous technological innovation in semiconductor IPs and EDA tool integration.

• Design, develop, and deploy GenAI Agentic and machine learning models, algorithms, and systems to tackle complex business challenges;
• Provide technical leadership and mentorship, supporting junior engineers and data scientists in best practices and advanced techniques;
• Apply the latest AI, Agentic AI, and machine learning advancements to enhance existing systems or develop innovative solutions;
• Collaborate with program and product managers, software engineers, and stakeholders to define requirements and create technical specifications for AI solutions;
• Conduct data analysis, preprocessing, and feature engineering to prepare datasets for machine learning models;
• Train, validate, and fine-tune machine learning models to meet performance and accuracy benchmarks;
• Deploy AI models into production environments, monitoring and optimizing their performance;
• Document models, algorithms, and methodologies to ensure reproducibility and facilitate knowledge sharing;
• Ensure all AI solutions comply with ethical guidelines, data privacy regulations, and industry standards.

• Ph.D. or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a related field;
• Minimum 8 years of experience in software engineering, machine learning, and GenAI, with a proven track record in production deployments;
• Strong proficiency in Python;
• Expertise in data structures, algorithms, and design patterns for scalable AI solutions;
• Extensive experience with machine learning and Agentic frameworks (e.g., TensorFlow, PyTorch, LangChain/LangGraph, AutoGen) and LLM models;
• Strong grasp of statistical analysis, data mining, and data visualization techniques;
• Knowledge of cloud platforms, containerization (Kubernetes, Docker), and version control systems (Git, P4);
• Familiarity with Agile, Kanban, or Scrum methodologies;
• Nice to have: Familiarity with backend and distributed systems, message queues, orchestration technologies, understanding or experience with semiconductor IPs and EDA tools.

• Comprehensive range of health, wellness, and financial benefits.