ABOUT THE PROJECT
View all jobsLead AI Infrastructure Engineer (Python/ML )USA, RemoteApply NowType: Long-term contract Location: Remote (overlap with PST) At Sphere, we partner with global logistics company leveraging AI, Machine Learning, and Data Engineering to optimize warehouse operations, predictive maintenance, and route planning. Role: Build and maintain scalable AI infrastructure, enabling teams to run ML experiments, deploy machine learning models, and implement MLOps pipelines for production-grade AI.
REQUIREMENTS
- 5+ years in Python and ML infrastructure
- Experience in cloud AI platforms (AWS Sagemaker, GCP AI Platform, Azure ML)
- Experience with containerization (Docker), orchestration (Kubernetes), and CI/CD for ML
- Experience with distributed systems, data pipelines, and high-performance computing for AI
- Hands-on with deep learning frameworks like TensorFlow or PyTorch
- Apply NowMore OpeningsNew Jersey, NJBrazil, RemoteMiami, RemoteUSA, RemoteRemotely, RemotelyShare This JobPowered by
RESPONSIBILITIES
- Design distributed training pipelines for large-scale machine learning and deep learning models
- Optimize compute and storage resources for cloud-based AI/ML workloads on AWS, GCP, or Azure
- Collaborate with data scientists and ML engineers to deploy models in production efficiently
- Implement monitoring, logging, and alerting for model performance and AI workflows
- Ensure scalable, maintainable, and reliable AI infrastructure to support real-time and batch ML applications
