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