Machine Learning Engineer

• Design and implement enterprise-scale ML infrastructure.
• Architect high-performance model serving solutions handling millions of predictions per second.
• Build robust, scalable systems for model training, serving and inferencing.
• Ability to write clean code in any programming language (Preferably Python).
• Lead technical decisions for critical ML platform components.
• Develop automated ML pipelines using “State of art” tools.
• Implement sophisticated monitoring and observability solutions.
• Optimize resource utilization across large scale distributed computing environments.
• Design fault-tolerant, highly available ML systems using Airflow or MLflow, HPC (SLURM)/ GPU.

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