Required Qualifications

• 8+ years of hands-on AI/ML experience.
• Master’s degree required; PhD preferred.
• Hands-on experience with AI/ML infrastructure and performance optimization, including GPU clusters, distributed training, inference-serving optimization, and MLOps pipelines.
• Strong experience in ML model and algorithm development, including model design, training, and evaluation.
• Experience taking ML models into production, including feature engineering, data pipelines, and deployment.
• Experience with hardware-aware ML, including optimizing inference engines for specific chips or adapting model architectures and quantization to hardware constraints.