Dev/ MLOps Engineer I (Full Stack)

Job Description Dev/ MLOps Engineer I (Full Stack)Location: HQ In PersonAbout Us:Origin is redefining home security with TruShield℠ Security, a hardware-free, router-based solution powered by our exclusive AI Sensing℠ technology. TruShield goes beyond motion detection to deliver Verified Human Presence℠, accurately distinguishing between people and non-human activity. By leveraging existing WiFi networks and connected devices, it delivers awareness across the home without cameras, wearables, or additional hardware, eliminating false alarms and elevating protection.Now part of ADT, Origin strengthens ADT's promise of trusted protection by adding real-time awareness and context inside the home. When every second counts, knowing what is actually happening, not just that something happened, changes everything.About the Job:We are looking for a Dev / MLOps Engineer I to build and support the infrastructure that powers our cloud applications and machine learning systems. In this role, you will work across the stack, contributing to frontend and backend services while building the DevOps and MLOps foundations that enable scalable, reliable, and automated product development.You will partner closely with product, engineering, and research teams to support CI/CD pipelines, cloud infrastructure, and machine learning workflows. This role is ideal for an early-career engineer who is interested in full-stack development and wants to grow into DevOps and MLOps while working on real-world AI systems.What You'll Do:Build, maintain, and optimize CI/CD pipelines to support application and ML workflowsDevelop and deploy containerized services using Docker and KubernetesSupport cloud infrastructure across AWS (preferred), with exposure to Azure or GCPImplement infrastructure-as-code using tools such as Terraform or CloudFormationContribute to the development of frontend interfaces and backend services for internal toolsBuild and maintain data and ML pipelines, including data ingestion, validation, training, and deploymentSupport model lifecycle management, including versioning, tracking, and performance monitoringImplement monitoring, logging, and alerting to ensure system reliability and observabilityConduct load and stress testing to evaluate performance and scalability of systemsDebug issues across the stack, including applications, infrastructure, and ML pipelinesCollaborate with research teams to support model development and productionization workflowsDrive automation to reduce manual processes across DevOps and ML systemsBuild and support infrastructure that powers AI systems deployed at scaleGain hands-on experience across full-stack development, DevOps, and MLOps environmentsCollaborate cross-functionally with product, research, and engineering teams to deliver production-ready systemsAbout You:Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field (Master's preferred)0–3 years of experience in software engineering, DevOps, or MLOpsStrong programming skills in Python, with experience in scripting (Bash) and SQLFamiliarity with CI/CD tools such as GitHub Actions, Jenkins, or similarExperience working with Docker and containerized environments (Kubernetes is a plus)Exposure to cloud platforms, especially AWS (EC2, S3, Lambda, etc.)Understanding of data pipelines and machine learning workflowsStrong problem-solving skills and ability to work in a fast-paced, collaborative environmentExcellent communication and interpersonal skillsNice to Have:Experience with ML platforms such as SageMaker or similar toolsFamiliarity with workflow orchestration tools (Airflow, Kubeflow)Exposure to monitoring tools (CloudWatch, Prometheus, Grafana)Experience with NoSQL databases or time-series data systemsExposure to JavaScript/TypeScript or backend API developmentExperience with IoT, sensor data, or distributed systems