MLOps Engineer

Job Summary

To develop tools and systems that enhance the ML models lifecycle in production, the full-time MLOps Engineer will create and optimize data pipelines, implement backend systems, and improve the development experience for Data Scientists in a remote environment.

Key responsibilities

• Develop tools for Data Scientists to scale their operations and routines
• Create and optimize data pipelines and systems for ML models
• Build and optimize ML and mathematical algorithms based on Data Science research

Required qualifications

• Education in STEM-related fields, preferably in Computer Science, Math, or Physics
• 5+ years of experience in Python programming
• Understanding of the ML models training lifecycle
• Familiarity with key ML principles and terms such as loss, training loop, and gradient descent