Data Engineer with MLOPS

Client: Capital One Job Title: Data Engineer with MLOPS Location: McLean, VA ( Need local Candidates) – Hybrid Duration: 10 Months Client: Previous Client Experience Pay Range: $70–75/hr on W2 Only Job Summary: We are seeking a highly skilled MLOps Engineer / Python Developer with strong experience in building and maintaining scalable data and machine learning pipelines. The ideal candidate will have hands-on expertise in Python, AWS, Kubernetes, and ML workflow tools (Kubeflow) along with solid experience in data processing frameworks like Spark and Pandas. Key Responsibilities: • Develop, maintain, and optimize data and model-serving pipelines using Kubeflow and Spark • Implement feature engineering workflows for machine learning models • Deploy, test, and monitor ML applications in cloud environments • Collaborate with Data Scientists and cross-functional teams to productionize models • Identify and fix bugs, vulnerabilities, and performance issues • Handle feature requests and enhancements for existing systems • Support and manage CI/CD pipelines and DevOps processes • Ensure system scalability, reliability, and security compliance Required Skills: • Strong programming experience in Python • Hands-on experience with AWS (or similar cloud platforms) • Expertise in Kubernetes and Kubeflow (or similar orchestration/workflow tools) • Experience with Spark, Pandas, NumPy for data processing • Solid understanding of MLOps, ML lifecycle, and feature engineering • Familiarity with CI/CD tools (Jenkins or similar) • Experience in debugging, performance tuning, and vulnerability remediation