Synopsys

We Are:

At Synopsys, we drive innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence, powering everything from self-driving cars to advanced learning machines. Join us to transform the future through continuous technological innovation.

You Are:

You are a seasoned DevOps/MLOps professional with deep expertise in building scalable, reliable platforms for AI development and deployment. You thrive in collaborative environments, lead by example, and have a passion for operational excellence and continuous learning. Your ability to design and operate CI/CD pipelines, containerized platforms, and ML workflows sets you apart. You’re a skilled communicator, mentor, and problem-solver, ready to make a significant impact at Synopsys.

What You’ll Be Doing:

• Design, develop, and own CI/CD pipelines and release processes for AI, GenAI, and Agentic systems—including services, tools, libraries, and infrastructure.
• Lead the installation, configuration, deployment, and lifecycle management of AI and Agentic tools across development, staging, and production environments.
• Build and operate cloud-native platforms using Docker and Kubernetes, managing deployments, scaling, upgrades, and environment standardization.
• Develop robust MLOps workflows: automated ML training pipelines, model packaging, reproducibility, artifact tracking, and promotion across environments.
• Create and maintain Generative AI and Agentic AI evaluation infrastructure (benchmarking, regression testing, quality gates, and reporting).
• Build infrastructure and pipelines for large-scale data collection, storage, and processing to support training, fine-tuning, and evaluation.
• Partner closely with AI engineers, data scientists, software engineers, and program/product managers to define requirements, write technical specifications, and ensure successful delivery.
• Implement observability practices (monitoring, logging, tracing, alerting) for ML systems and platform services; drive reliability improvements through SLOs and incident learnings.
• Establish infrastructure-as-code and configuration management best practices to ensure consistent, auditable, and repeatable environments.
• Provide technical leadership and mentorship to engineers, driving best practices in DevOps/MLOps, security, and operational readiness.

The Impact You Will Have:

• Enable rapid experimentation and deployment of AI and Agentic solutions by evolving DevOps capabilities into world-class MLOps practices.
• Drive operational excellence, reliability, and security across all AI platform services and infrastructure.
• Empower teams to deliver high-quality, scalable AI products through robust automation, reproducibility, and best practices.
• Accelerate the innovation cycle for AI/ML initiatives, supporting faster time-to-market and continuous improvement.
• Establish standards for infrastructure, data pipelines, and evaluation frameworks that ensure consistency and transparency.
• Lead by example, mentoring engineers and fostering a culture of learning, collaboration, and technical excellence.
• Champion observability and incident management practices that drive reliability and customer satisfaction.
• Shape the future of AI at Synopsys by contributing to the development of cutting-edge tools, platforms, and processes.

What You’ll Need:

• Ph.D. or Master’s degree in Computer Science, Software Engineering, Data Science, Electrical Engineering, or related field (or equivalent practical experience).
• Minimum of 8 years of experience in DevOps/SRE/Platform Engineering, with ownership of production CI/CD and deployment systems.
• Strong experience building CI/CD pipelines and release automation (e.g., Jenkins, GitHub Actions, GitLab CI, Argo CD, Tekton).
• Hands-on expertise with containerization and orchestration: Docker and Kubernetes (deployments, configuration, security, scaling).
• Experience building ML training and/or MLOps pipelines (workflow orchestration, artifact/version management, reproducibility).
• Strong proficiency in scripting and automation (e.g., Python, Bash) and solid software engineering fundamentals.
• Experience designing scalable data infrastructure for large volumes (e.g., Snowflake, data lakes, and large databases/search systems such as Elasticsearch).
• Knowledge of cloud and/or on-prem infrastructure operations, networking fundamentals, secrets management, and access control.
• Familiarity with version control systems (e.g., Git, P4) and software development methodologies (e.g., Agile, Kanban, Scrum).
• Experience with Generative AI / Agentic systems operationalization (deployment patterns, evaluation, monitoring) is a strong plus.

Who You Are:

• Excellent problem-solving and analytical skills.
• Strong communication and interpersonal skills.
• Ability to work independently and as part of a team.
• Proven leadership and mentorship abilities.
• Adaptable, proactive, and eager to learn new technologies.
• Collaborative, inclusive, and committed to fostering a diverse team environment.

The Team You’ll Be A Part Of:

Join a dynamic and collaborative group of professionals dedicated to advancing AI, GenAI, and Agentic technologies. Our team is focused on building scalable, reliable platforms that support end-to-end ML training and evaluation at scale. You’ll work alongside AI engineers, data scientists, software engineers, and program/product managers, partnering to deliver impactful solutions that drive innovation across Synopsys’ AI portfolio. We value creative problem-solving, continuous improvement, and a supportive, inclusive team culture.

Rewards and Benefits:

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.