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ML Ops Engineer
Job in
El Segundo, Los Angeles County, California, 90245, USA
Listed on 2026-07-24
Listing for:
Towards AI, Inc.
Full Time
position Listed on 2026-07-24
Job specializations:
-
IT/Tech
Data Engineering, Machine Learning/ ML Engineer, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below
Python S3
SQLTriton### Key skills
Data Engineer Data InfrastructureML Research Training Data Machine LearningML Ops Data Science
IntegrationsCICDDistributed Systems Data Processing Data Quality Automated Testing Data Warehousing Git Hub Actions Operations Deployment Backend Cloud Reliability Batch Inference Embedded Logging Storage Architecture Security SOCDevops
AutomationIAMDebugging Streaming Startup AIGoogle Analytics### Tools, Libraries and FrameworksAirflowAWSFirmWareMLFlowEC2
Snow Flake Cloud Watch Docker Jenkins DVCApache Spark Ruby On Rails Tensorflow Dask ## Description The role involves owning the infrastructure and operational lifecycle of machine learning systems for a clinical monitoring platform. The engineer will build and maintain production pipelines, deployment infrastructure, and monitoring systems to support predictive models. Responsibilities include managing model versioning, experiment tracking, and ensuring the reliability of training and deployment workflows.
The position requires collaborating across various technical and clinical teams to facilitate the transition from experimentation to production. Additionally, the role focuses on implementing operational observability, data versioning, and infrastructure-as-code to ensure system scalability and performance.##
Required Qualifications and Skills Candidates must possess at least four years of experience in MLOps, ML engineering, Dev Ops, or a related infrastructure role. Proficiency in Python, Apache Airflow, MLflow, and AWS services is required, alongside experience with containerization and infrastructure-as-code. Applicants should have a solid understanding of the machine learning lifecycle, including training, deployment, and monitoring. While no specific degree is mentioned, the role requires strong debugging skills and familiarity with SQL and data warehousing platforms.
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