> Markdown version of [/jobs/ext/569029-sr-software-engineer-mlops](https://www.wearedevelopers.com/jobs/ext/569029-sr-software-engineer-mlops). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Software Engineer, MLOps - **Company:** Vivint, Inc. - **Location:** Washington, DC, United States - **Experience:** Expert - **Salary:** $150,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Cloud Engineering, Cyber Security, Continuous Integration, Data Validation, Python (Programming Language), Machine Learning, Recommender Systems, Azure Machine Learning, Software Engineering, Management of Software Versions, Large Language Models, Git, AI Platforms, Kubernetes, Information Technology, Low Latency, Google Cloud Functions, Machine Learning Operations, Virtual Agents - **Published:** June 14, 2026 - **Apply:** https://www.careerjet.com/jobad/use3e3f6b5a849f485d484640a5feb3afa ## About the Role * Bachelor's degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 5+ years of professional experience in software development, applied science, or ML engineering; or * Master's degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 2+ years of professional experience in software development, applied science, or ML engineering * Experience building production ML platforms, model serving systems, or MLOps workflows * Strong Python and cloud engineering skills * Experience with CI/CD, Git, infrastructure-as-code, and production monitoring * Familiarity with model registry, , validation, deployment, rollback, and observability * Ability to communicate tradeoffs clearly across engineering, data science, and product teams Preferred Qualifications: * Experience with GCP/AWS, Cloud Run, Kubernetes, Vertex AI, SageMaker, MLflow, or equivalent tools * Experience with AI services for computer vision, LLMs, multimodal models, or recommendation systems * Experience with data validation, dataset versioning, feature stores, or model quality monitoring * Experience optimizing cost, latency, reliability, and operational readiness for AI systems * Experience with IoT, edge AI, smart home, or distributed device environments ## Description We are seeking a Sr MLOps Engineer to build the model lifecycle, deployment, observability, and infrastructure foundations used by multiple production AI features, including recognition, AI Video Search, Multimodal AI, Agentic AI, and Energy AI ship faster with shared, reliable platform primitives. In this role, you will be responsible for: * Build model registry, model serving, deployment, rollback, and CI/CD systems for production AI services. * Own feature, dataset, model, and prompt versioning patterns across AI products. * Standardize training, evaluation, release, monitoring, and operational workflows for AI teams. * Improve reliability, cost efficiency, latency, and repeatability of AI launches. * Create reusable platform patterns across AI features * Partner with engineering, data science, product, and operations teams to productionize AI capabilities at scale., This role focuses on enhancing the safety of advanced AI models through cybersecurity expertise. As a cybersecurity software engineer, you will leverage your skills to assess and i… + Just now + Apply easily, This role offers an exciting opportunity to take ownership of core internal platform systems, contributing to their design and development from end to end. As a Software Engineer o… + 22 hours ago + Apply easily ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [MLOps - What’s the deal behind it?](https://www.wearedevelopers.com/videos/392-mlops-what-s-the-deal-behind-it) ## Related Articles - [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 – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)