Marina del Rey, CA30+ days ago
Key Responsibilities: • Lead, mentor, and grow a team of Machine Learning Engineers, fostering a culture of innovation and continuous improvement • Design and implement scalable ML infrastructure for model training, deployment, and serving • Establish and enforce best practices for ML model lifecycle management, including versioning, testing, and monitoring • Develop and maintain CI/CD pipelines for machine learning workflows • Optimize model inference performance and reduce latency/cost across production systems • Collaborate with ML Engineers and Data Scientists to productionize models efficiently • Implement robust monitoring, alerting, and observability solutions for ML systems • Drive technical decisions on ML Ops tooling, infrastructure, and architecture • Ensure high availability and reliability of ML services at scale • Manage project timelines, priorities, and resource allocation for the ML Ops team. • Experience with ML experiment tracking, model versioning, and feature stores • Strong understanding of CI/CD principles applied to ML workflows • Experience optimizing model inference performance (ONNX, TensorRT, or similar) • Excellent leadership, communication, and stakeholder management skills • Track record of building and scaling high-performing engineering teams • Openness to new technologies and creative solutions.