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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cloud MLOps Engineer - **Company:** Insight Global - **Location:** Austin, TX, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Bash Shell, Cloud Computing, Cloud Engineering, Continuous Integration, Python (Programming Language), Machine Learning, Robotic Automation Software, Software Deployment, Data Streaming, Management of Software Versions, Scripting, Kubernetes, Apache Kafka, Azure AKS, Slurm, Machine Learning Operations - **Published:** July 23, 2026 - **Apply:** https://dejobs.org/x/x/CF95FC7DBA42432B86E587144DF943ED/job/ ## About the Role Strong experience with cloud platforms: AWS, GCP, and/or Azure Hands-on experience operating Kubernetes or managed Kubernetes services in production Experience building or maintaining MLOps platforms supporting training and inference Familiarity with ML experiment tracking and orchestration tools (e.g., MLflow, Weights & Biases, Slurm, Ray, Kubeflow, or similar) Experience deploying ML models into production-facing applications or services Strong understanding of CI/CD, infrastructure-as-code, and automation Proficiency in Python; experience with Bash or another scripting language Ability to collaborate effectively across research and engineering teams Experience working with robotics or real-time telemetry data Familiarity with streaming data systems (e.g., Kafka, Pub/Sub, Kinesis) Experience supporting GPU workloads in cloud or Kubernetes environments Exposure to edge-cloud ML deployment or fleet-based systems Prior work in robotics, autonomy, or embodied AI environments ## Description We are seeking a Cloud MLOps Engineer to build and operate the cloud infrastructure that powers machine learning for a humanoid robotics platform. This role sits at the intersection of ML research, production systems, and end-user applications, with a strong focus on robot telemetry data, model lifecycle management, and production deployment. You will enable researchers and applied ML engineers to reliably train, evaluate, and deploy models at scale, while ensuring telemetry-driven insights flow from robots in the real world back into continuous learning systems. What You'll Do Design, deploy, and maintain cloud-native MLOps platforms supporting large-scale ML training, evaluation, and inference workloads Operate Kubernetes-based infrastructure (self-managed or managed services such as GKE, EKS, or AKS) for ML workloads and data applications Build and maintain end-to-end ML pipelines that bridge research workflows with production systems Support robot telemetry ingestion, processing, and analytics, enabling model feedback loops from deployed humanoid robots Integrate and operate ML tooling such as MLflow, Weights & Biases, Slurm, or similar systems for experiment tracking, scheduling, and reproducibility Enable model deployment to production, including CI/CD for models, versioning, monitoring, and rollback strategies Partner closely with ML researchers, perception, controls, and applications teams to productionize models safely and efficiently Implement observability across ML systems, including model performance, data drift, and system health Improve reliability, scalability, and security of cloud ML infrastructure supporting real-world robotic systems We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. ## Related Videos - [Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬](https://www.wearedevelopers.com/videos/100355-running-secure-life-science-research-at-scale-using-hybrid-gpu-hpc-and-kubernetes) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Azure-Well Architected Framework - designing mission critical workloads in practice](https://www.wearedevelopers.com/videos/1529-azure-well-architected-framework-designing-mission-critical-workloads-in-practice) - [JavaScript? No. Java Scripts! - Scripting with Java](https://www.wearedevelopers.com/videos/2094-javascript-no-java-scripts-scripting-with-java) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Azure-Well Architected Framework - Cost Optimization in practice](https://www.wearedevelopers.com/videos/2100-azure-well-architected-framework-cost-optimization-in-practice) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [Got AI ideas but no money? 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