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.