{"schemaVersion":"jobsearcher.job.v1","id":"d85efa3f27276f256709871c","url":"https://jobsearcher.com/jobs/d85efa3f27276f256709871c","canonicalUrl":"https://jobsearcher.com/jobs/d85efa3f27276f256709871c","title":"Python Developer","description":"Job Description\n\nPython Developer Onsite RoleCharlotte NCKey Responsibilities • Build and maintain large-scale data processing pipelines using Apache Spark for batch and streaming data. • Design and implement ML training and inference workflows using PyTorch and integrate them into production systems. • Develop and orchestrate ETL and ML pipelines with Apache Airflow, ensuring reliability, scalability, and observability. • Optimize performance of data pipelines and ML model training on distributed clusters. • Collaborate with Data Scientists and ML Engineers to productize models and deploy them into production environments. • Implement best practices for code quality, CI/CD, unit testing, and monitoring. • Ensure data quality, integrity, and security across all pipelines. • Troubleshoot performance bottlenecks and optimize resource utilization. • Stay up to date with advancements in ML frameworks, distributed computing, and workflow orchestration tools.Required Qualifications • Bachelor's or Master's degree in Computer Science, Engineering, or related field. • 5+ years of professional Python development experience, with strong object-oriented programming and software engineering fundamentals. • Hands-on experience with PyTorch for model training and inference. • Deep understanding of Apache Spark for distributed data processing (PySpark or Scala is a plus). • Strong experience with Apache Airflow for workflow orchestration in production environments. • Proficiency in SQL and working with relational and NoSQL databases. • Experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure). • Familiarity with data versioning and ML model lifecycle management (MLflow or similar). • Strong problem-solving and debugging skills in distributed systems. Preferred Skills • Experience with real-time data processing frameworks (Kafka, Flink). • Knowledge of feature stores, data lake architectures, and Delta Lake. • Familiarity with MLOps practices (CI/CD for ML, model registry, automated retraining). • Experience with GPU-accelerated ML training and performance optimization. • Contribution to open-source ML or data engineering projects.","company":"Rapid Eagle","rawCompany":"rapid eagle","city":"Charlotte","state":"NC","isRemote":false,"isActive":false,"createdAt":"2026-05-24T08:00:42.144Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Python Developer","description":"Job Description\n\nPython Developer Onsite RoleCharlotte NCKey Responsibilities • Build and maintain large-scale data processing pipelines using Apache Spark for batch and streaming data. • Design and implement ML training and inference workflows using PyTorch and integrate them into production systems. • Develop and orchestrate ETL and ML pipelines with Apache Airflow, ensuring reliability, scalability, and observability. • Optimize performance of data pipelines and ML model training on distributed clusters. • Collaborate with Data Scientists and ML Engineers to productize models and deploy them into production environments. • Implement best practices for code quality, CI/CD, unit testing, and monitoring. • Ensure data quality, integrity, and security across all pipelines. • Troubleshoot performance bottlenecks and optimize resource utilization. • Stay up to date with advancements in ML frameworks, distributed computing, and workflow orchestration tools.Required Qualifications • Bachelor's or Master's degree in Computer Science, Engineering, or related field. • 5+ years of professional Python development experience, with strong object-oriented programming and software engineering fundamentals. • Hands-on experience with PyTorch for model training and inference. • Deep understanding of Apache Spark for distributed data processing (PySpark or Scala is a plus). • Strong experience with Apache Airflow for workflow orchestration in production environments. • Proficiency in SQL and working with relational and NoSQL databases. • Experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure). • Familiarity with data versioning and ML model lifecycle management (MLflow or similar). • Strong problem-solving and debugging skills in distributed systems. Preferred Skills • Experience with real-time data processing frameworks (Kafka, Flink). • Knowledge of feature stores, data lake architectures, and Delta Lake. • Familiarity with MLOps practices (CI/CD for ML, model registry, automated retraining). • Experience with GPU-accelerated ML training and performance optimization. • Contribution to open-source ML or data engineering projects.","datePosted":"2026-05-24T08:00:42.144Z","dateModified":"2026-05-24T08:00:42.144Z","hiringOrganization":{"@type":"Organization","name":"Rapid Eagle","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Charlotte","addressRegion":"NC","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"d85efa3f27276f256709871c"},"url":"https://jobsearcher.com/jobs/d85efa3f27276f256709871c"}}