Lead AI Infrastructure Engineer; Python​/ML

Overview

Type: Long-term contract
Location: Remote (overlap with PST)

At Sphere
, we partner with a 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.

• 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.

• 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 Tensor Flow or PyTorch.