Machine Learning Ops Engineer

Project overview

Position: MLOps ( Python Cor, ML engineer)

Requirements

Python, Azure, ML, AKS, PyTorch

Here is JD below:

• Hands-on experience developing, fine-tuning, and deploying ML and foundation models in production.
• Strong Python skills and expertise with PyTorch and/or TensorFlow.
• Experience building and operating MLOps pipelines, including CI/CD, model lifecycle management, and monitoring.
• Experience deploying ML workloads on Azure and Kubernetes (AKS).
• Strong software engineering practices, including testing, code quality, and automation.
• Ability to work effectively with ML researchers, data scientists, and cross-functional engineering teams.
• Experience managing multi-GPU-based workloads and optimizing model performance.

Nice to have

Job Facts: Contract W2 | On-site | Depends on Experience

Skills: GPU, Continuous Integration, Kubernetes, Machine Learning Operations (ML Ops), PyTorch, Python, Machine Learning (ML), Continuous Delivery, Microsoft Azure, Management, TensorFlow

Reference: Dice Id: 10125301 | Position Id: EP266598

• Experience with distributed training frameworks and large-scale model training.
• Familiarity with ML platform engineering, including training infrastructure and workload orchestration.
• Exposure to platform operations, reliability, governance, and compliance requirements.
• Experience mentoring engineers or leading technical initiatives.

Project details

USA any, or Ideally San Jose, CA; San Diego, CA; Wilton, CT

12+Months

• Start: flexible
• Remote: onsite
• Location: San Diego, CA, US, US