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