Description

You will build, deploy, and maintain machine learning models and the underlying infrastructure required to support them.

Responsibilities

• Develop and deploy machine learning models, tools, and automated workflows to ensure reliability and scalability.
• Monitor model performance and troubleshoot issues to maintain high availability.
• Collaborate with data science, engineering, and operations teams to enhance ML infrastructure.
• Implement security best practices for ML systems and maintain documentation for all workflows and processes.
• Manage infrastructure risks by developing mitigation plans and escalating unresolved issues.

Required Skills

• 5+ years of experience in machine learning operations or related engineering roles.
• Proficiency with Python, Conda, and Docker.
• Experience managing workloads with Slurm.
• Hands-on experience with ML tools including Jupyter, MLFlow, RunAI, and Nvidia Global Catalog (NGC).
• Proven track record of deploying and maintaining machine learning models in production.
• Experience building and managing CI/CD pipelines and automation tools.
• Ability to manage technical, product, and vendor stakeholders independently.
• Strong documentation and technical communication skills.

Preferred Skills

• Experience with Azure or Google Cloud platforms.
• Knowledge of Kubernetes.
• Experience with PyTorch, torchrun, or TorchX.

Key Skills

Education

Any Gradute