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

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.

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.

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.

Senior MLOPS Engineer - AIML

Senior Mlops Engineer