Machine Learning Ops Engineer

You will own the ML operational lifecycle from training to production deployment.ResponsibilitiesDeploy high throughput ML models into production environments.Manage and deploy custom applications, including those without Docker containers.Build and maintain development, testing, and production deployment pipelines.Provide technical guidance on NLP, Machine Learning, and Statistical Methods.Required Skills7+ years experience with a Bachelor's Degree, or 5+ years experience with a Master's Degree.Expert proficiency in Python.Experience managing ML model performance, including memory management and debugging.Proficiency in SQL (PostgreSQL) and NoSQL (MongoDB).Experience understanding the full ML development lifecycle (labeling, training, testing, deployment, monitoring).Experience with ML frameworks: Tensorflow, Pytorch, ONNX, Scikit-learn, Pandas.Experience with version control (Git) and regular expressions.Ability to formulate and rapidly prototype approaches and communicate trade-offs.