{"n":"Ai Engineer & Researchers","p":40,"c":12,"o":10,"m":128800,"h":62,"a":85,"rg":[["EMEA",40],["Americas",34],["APAC",26]],"b":[["Junior",8,69000,80000,93000],["Mid-level",42,93000,108000,125000],["Senior",30,114000,133000,154000],["Lead",14,128000,149000,173000],["Principal",6,157000,183000,212000]],"rl":[["AI Data Trainers","ai-data-trainers",40],["AI Product Engineers","ai-product-engineers",40],["Cloud Engineering Managers","cloud-engineering-managers",40],["Community Engineers","community-engineers",40],["Developer Success Engineers","developer-success-engineers",40],["Enterprise Presales Engineers","enterprise-presales-engineers",40]],"r":[["Loki","Webflow E-Commerce Developer","Americas",100,118,189300],["Wanda Maximoff","Senior Webflow Developer","EMEA",100,128,205000],["Scott Lang","Enterprise Webflow Developer","EMEA",100,101,162050],["Dr. Stephen Strange","Webflow Frontend Developer","APAC",100,74,119050],["The Visionary","Lead Production Engineer","APAC",99,46,95000],["The Titan","Lead Unreal Programmer","APAC",99,77,160000],["Batman","Principal Software Engineer","EMEA",99,77,160000],["Grace","Principal Research Engineer","EMEA",99,62,130000],["The Innovator","Principal Quality Engineer","APAC",99,67,140000],["The Mentor","Lead Developer","Americas",99,72,150000],["The Wise Mentor","Technical Architect","Americas",99,72,150000],["Toast","Test Architect","APAC",99,72,150000]],"j":[["Data Preparation and Preprocessing",["Cleaning and normalizing datasets for model training.","Handling missing values through imputation or deletion.","Feature selection and engineering to improve model performance.","Encoding categorical variables into numerical format."]],["Model Development and Training",["Designing neural network architectures for specific tasks.","Implementing training loops and optimization algorithms.","Conducting hyperparameter tuning for model improvement.","Validating model performance using cross-validation techniques."]],["Model Evaluation and Optimization",["Generating performance metrics such as accuracy and F1 score.","Identifying overfitting through learning curve analysis.","Running A/B tests to compare model effectiveness.","Implementing techniques for model interpretability and explainability."]],["Deployment and Maintenance",["Containerizing models using Docker for deployment.","Setting up CI/CD pipelines for automated deployments.","Monitoring model performance in production environments.","Updating models with new data or improved algorithms."]]]}