Description

You will operationalize AI solutions at scale by managing the machine learning lifecycle and production pipelines.

Responsibilities

• Build scalable infrastructure for ML models to ensure seamless production integration.
• Develop and maintain CI/CD pipelines focused on ML model deployment.
• Deploy models using TensorFlow Serving, PyTorch Serving, Triton Inference Server, or TensorRT and monitor production performance.
• Collaborate with data scientists and software engineers to transition models from research to production.
• Uphold security protocols and ensure regulatory compliance within ML systems.

Required Skills

• 4-6 years of experience in ML project management with a recent focus on MLOps.
• Proficiency in Docker and Kubernetes for containerization and orchestration.
• Experience with CI/CD pipeline development and maintenance.
• Hands-on experience deploying models via TensorFlow Serving, PyTorch Serving, Triton Inference Server, or TensorRT.
• Experience with cloud platforms including AWS, Azure, or GCP.
• Knowledge of AI technologies deployment, data engineering, and scalability testing.
• Familiarity with security practices and IT performance.
• Any graduate degree in Computer Science, Engineering, or a related field.

Key Skills

Education

ANY GRADUATE