Applied AI Engineer II

Role:

• Own the infrastructure that keeps ML models running reliably in production.
• Bridge the gap between experimentation and production by turning research artifacts into robust, monitored services.
• Shape on-premises MLOps practices and improve engineering across the ML stack.

Ideal Candidate:

• 3+ years of experience in MLOps or full stack Machine Learning.
• Strong programming skills in Python, scientific Python stack, and Cuda.
• Experience with Kubernetes, cloud platforms, CI/CD, and data management.

Benefits:

• Competitive salary and annual bonus.
• Medical, life, and accidental insurance.
• Vacation and leaves including menstrual, flexible, and special leaves.