USA_Developer

AI/ML roles focus on designing, building, and deploying intelligent systems that learn from data to solve complex problems. Machine Learning Engineers sit between data science and software engineering, writing scalable code to deploy, optimize, and maintain ML models in production. MLOps Engineers manage the underlying infrastructure, building continuous integration and deployment (CI/CD) pipelines to automate model monitoring, data versioning, and system scaling.

Prompt emgineering, Forward-Deployed Engineer, Python, R, C .Mathematics: Linear algebra, calculus, statistics.Data Handling: SQL, data preprocessing.Frameworks: TensorFlow, PyTorch, Scikit-Learn.M LOps: Model deployment, cloud platforms.

Desirable skills: MLOps tools (Docker, Kubernetes, MLflow)Data pipeline development (Spark, SQL, Airflow)System design and architectureCloud computing platforms (AWS, GCP, Azure)Cross-functional communication and storytelling

Skills: Digital : Machine Learning~Digital : Artificial Intelligence(AI)

Experience Required: 8-10 years

Skills:CategoryNameRequiredImportanceExperienceSkillCategoryTest1_MNDigital : Machine LearningYes1>7 years