MLOps Engineer

Location: San Francisco, CA, USA (Hybrid/Remote)

Job Type: Full-Time

About the Role

We are seeking an experienced MLOps Engineer to build and manage scalable machine learning infrastructure, automate model deployment pipelines, and ensure reliable operation of production AI systems. You will work closely with Data Scientists, ML Engineers, and DevOps teams to streamline the ML lifecycle.

Key Responsibilities

• Build and maintain machine learning pipelines.
• Deploy and monitor ML models in production.
• Automate model training, testing, and deployment workflows.
• Implement CI/CD pipelines for machine learning applications.
• Monitor model performance and data drift.
• Optimize cloud infrastructure for AI workloads.
• Collaborate with Data Scientists and Software Engineers.
• Maintain documentation and operational standards.

Required Qualifications

• Bachelor''s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Strong Python programming skills.
• Experience with cloud platforms and containerization.
• Understanding of machine learning workflows and model deployment.
• Strong problem-solving and communication skills.

Preferred Skills

• Python
• MLflow
• Kubeflow
• Docker
• Kubernetes
• AWS
• Azure
• Google Cloud Platform (Google Cloud Platform)
• TensorFlow
• PyTorch
• Airflow
• Jenkins
• Terraform
• Git
• CI/CD
• Linux

Benefits

• Health Insurance
• Paid Time Off
• Flexible Work Schedule
• Learning & Certification Support
• 401(k)
• Career Growth Opportunities

Visa Authorization Questions (Use for All Roles)

1. Are you legally authorized to work in the United States?
   • Yes
   • No
2. Will you now or in the future require employer sponsorship for employment visa status (e.g., H-1B, TN, etc.)?
   • Yes
   • No
3. What is your current work authorization status?
   • U.S. Citizen
   • Permanent Resident ()
   • H-1B
   • H-4 EAD
   • TN Visa
   • L-2 EAD
   • Other (Please Specify)