Senior ML Ops Engineer

What you'll do

• Analyze and profile machine learning models to identify performance bottlenecks and optimization opportunities.
• Implement optimization techniques such as quantization, pruning, distillation, and neural architecture search.
• Develop and integrate specialized libraries for efficient model execution on GPUs, CPUs, and edge devices.
• Design and conduct experiments to measure the impact of optimizations on model accuracy and speed.
• Automate model optimization workflows and build robust CI/CD pipelines for production deployment.
• Ensure the scalability and reliability of optimized models in production environments.
• Contribute to the continuous improvement of MLOps infrastructure for model deployment and monitoring.

What we're looking for

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
• 3+ years of experience in machine learning engineering, with a focus on model optimization and deployment.
• Proficiency in Python and strong programming skills.
• Experience with machine learning frameworks like TensorFlow or PyTorch and optimization libraries.
• Experience with cloud platforms (AWS, Azure, GCP) and deploying ML models in cloud environments.
• Familiarity with version control systems like Git and agile development methodologies.
• Master's degree in Computer Science, Data Science, or a related quantitative field (preferred).
• 5+ years of industry experience in ML Model Optimization, ML Engineering, or MLOps, particularly with large-scale 2D/3D computer vision models (preferred).