ML.NET/DevOps Engineer//USC//Active Public Trust Clearance

Job Description: ML/DevOps Engineer Location: Remote Contract Work Authorization: U.S. Citizen (USC) Clearance Requirement: Active Public Trust Clearance Required Technical Skills ML.NET: 6+ years of experience ML Model Architecture: 6+ years of experience DevOps: 6+ years of experience Role Overview The ML/DevOps Engineer will address complex infrastructure and machine learning challenges by combining machine learning expertise with DevOps engineering capabilities. The engineer will collaborate with the data science team to productionize machine learning capabilities and features, transforming point cloud and computer vision (CV) models into reliable, scalable services within a complex, event-driven architecture. The ideal candidate will have strong experience deploying and scaling services across cloud environments, with expertise in container orchestration, Infrastructure as Code (IaC), and observability for distributed pipelines. The role also requires an understanding of machine learning operations (MLOps), including model versioning, experiment tracking, and inference optimization, with knowledge of GPU/CPU trade-offs and ONNX-style runtimes.

Key Responsibilities

Collaborate with data scientists to deploy and productionize machine learning models and features. Convert point cloud and computer vision (CV) models into reliable, scalable production services. Design, deploy, and scale services across cloud environments. Support complex, event-driven architectures and distributed processing pipelines. Implement and maintain container orchestration and Infrastructure as Code (IaC) solutions. Establish observability, monitoring, and troubleshooting practices for distributed services. Support MLOps practices, including model versioning and experiment tracking. Optimize model inference performance by evaluating GPU/CPU utilization and ONNX-style runtimes. Bridge the gap between machine learning development and production infrastructure to ensure reliable ML-driven capabilities. Required Qualifications 6+ years of experience with ML.NET. 6+ years of experience in machine learning model architecture. 6+ years of DevOps experience. Experience deploying and scaling services in cloud environments. Knowledge of container orchestration, Infrastructure as Code, and observability. Understanding of MLOps, model versioning, experiment tracking, and inference optimization. Familiarity with point cloud processing, computer vision models, and event-driven architectures. U.S. Citizenship and an active Public Trust clearance. Ayush Sharma Sr. US Technical Recruiter | Ext:149 | G-talk: