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# CV/ML Platform Engineer

- **Company:** Allen Control Systems
- **Location:** Austin, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Computer Vision, Ubuntu (Operating System), Computer Clusters, Nvidia CUDA, Computer Programming, Continuous Delivery, Continuous Integration, Debian Linux, Linux, DevOps, Machine Learning, Prometheus, Azure Machine Learning, Software Systems, Management of Software Versions, Weka, Ceph (Software), Graphics Processing Unit (GPU), Robot Operating System, Grafana, Model Validation, Discretization, Kubernetes, ONNX (Open Neural Network Exchange) Format, Machine Learning Operations, Tools for Reporting, TensorRT, Hardware Infrastructure, NVIDIA Jetson, Software Version Control, Data Pipelines
- **Published:** November 7, 2026
- **Apply:** https://www.careerbuilder.com/job-details/cv-ml-platform-engineer-austin-tx--4833bc27-ecf8-4a69-8584-4f0dc7174a97

## About the Role

Startup, Control Systems, Computer Vision, Unmanned Aircraft Systems (UAS), Electrical Engineering, Robotics Software, GPU (Graphics Processing Unit), Machine Learning, Data Modeling, Continuous Deployment/Delivery, * 2+ years of experience in Platform Engineering or DevOps/MLOps.

 * Strong programming skills are required for automating ML lifecycles and building custom CLI tools for CV engineers.
 * Hands-on experience with NVIDIA GPU infrastructure, including managing CUDA libraries and development environments, GPU Operator, device plugins, and scheduling (MIG, Volcano, or fractional GPU sharing).
 * Experience implementing and maintaining MLOps platforms such as Kubeflow, MLflow, Weights & Biases (W&B), or DVC for experiment tracking and model versioning.
 * Familiarity with high-performance storage solutions (e.g., MinIO, WEKA, or Ceph) and data orchestration tools capable of handling terabytes of video/image data.
 * Proven track record building CI/CD pipelines that include automated model validation, performance benchmarking, and artifact management for both cloud and edge targets.
 * Experience with model optimization toolchains, including TensorRT, ONNX, and quantization techniques, specifically for cross-compilation to ARM targets like NVIDIA Jetson.
 * Proficiency with observability stacks (ELK, Prometheus/Grafana) adapted for ML, including monitoring GPU health, training throughput, and model inference metrics.
 * Strong Linux systems knowledge (Debian/Ubuntu), including networking for high-throughput data, storage, and security hardening for defense-grade production environments.

## Description

We are seeking an experienced CV/ML Platform Engineer with specialization in Computer Vision and Machine Learning (CV/ML) to design, build, and own the data, model, and compute infrastructure powering ACS CV/ML team. You will help manage a 130+ GPU bare-metal Kubernetes cluster, own CV/ML CI/CD pipelines, and ensure ML model training proceeds at high volume with low friction.

What You'll Do:

 * Deploy and operate Kubernetes clusters on bare-metal infrastructure hosting 130+ NVIDIA GPUs, with hybrid burst capability to AWS for scalable compute and storage workloads.
 * Manage NVIDIA GPU clusters for ML training.
 * Own the ACS CV/ML CI/CD pipeline.
 * Improve and maintain core ML infrastructure, such as model registration and versioning, experiment tracking, and model and data provenance tracking.
 * Improve and maintain ML model testing, performance analysis, and reporting tools.
 * Automate repetitive model training and testing tasks to increase developer velocity.
 * Work with Software Team Platform Engineers to ensure efficient coordination and minimal duplication between CV/ML infrastructure and wider Software infrastructure.
 * Collaborate with the Software Team to automate the optimization of models (TensorRT/quantization) for deployment on NVIDIA Jetson and other edge hardware.