MLOps Engineer - Build & Deploy ML Pipelines (Hybrid)

Tekfortune Inc.; North Dakota; Hybrid; USD 120,000 - 170,000; Full time

Job summary

Tekfortune Inc. in McLean, VA seeks a Machine Learning/MLOps Engineer to maintain and develop ML serving pipelines using Kubeflow, Spark, and Python. The role collaborates with Data Science teams on training pipelines, feature engineering, deployment, and CI/CD.

Hybrid on-site requirement; McLean preferred, New York possible; prior Capital One experience desirable; join a team of ML engineers focused on serving pipelines and enterprise integration.

Qualifications

• Experience with MLOps and ML tooling.
• Proficiency in Python.
• Knowledge of Kubernetes and AWS.
• Experience with Kubeflow or equivalent workflow tools.
• Familiarity with Spark, pandas, and NumPy.
• Hybrid on-site presence; McLean preferred (New York possible).
• Previous Capital One experience highly desirable

Responsibilities

• Maintain and develop ML serving pipelines using Kubeflow, Spark, and Python.
• Collaborate with Data Science teams on training pipelines and feature engineering.
• Develop features, deploy applications, test, and perform vulnerability fixes.
• Debug and support production ML pipelines and CI/CD workflows.
• Support integration across groups and enterprise.
• Build, train, and deploy machine learning models.
• Support models for credit card decisioning, fraud tracking, and risk assessment.

Skills

Python

AWS

Kubernetes

Kubeflow

Spark

pandas

NumPy

ML Ops tooling

Tools

Kubeflow

Jenkins

CI/CD pipelines

Databricks

mlplot

Job description

Tekfortune Inc. in McLean, VA seeks a Machine Learning/MLOps Engineer to maintain and develop ML serving pipelines using Kubeflow, Spark, and Python. The role collaborates with Data Science teams on training pipelines, feature engineering, deployment, and CI/CD.

Hybrid on-site requirement; McLean preferred, New York possible; prior Capital One experience desirable; join a team of ML engineers focused on serving pipelines and enterprise integration.