Senior Engineer - ML Ops

The measurement of your success will be based on cost savings, the impact of MLOps on business revenue, the number of projects successfully completed, improvements made to existing solutions and processes, and customer Net Promoter Score (NPS).

To qualify for the role you must have

• 10+ years experience in setting up and maintaining CI/CD pipelines, preferably in a machine learning context.
• Strong understanding of containerization and orchestration tools such as Docker and Kubernetes.
• Familiarity with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Proficient in scripting languages such as Python, Bash, or Shell for automation tasks.