MLOps - Englewood, CO 80111 --Onsite

Architect and implement scalable AWS ML/AI cloud infrastructure in a multi-tenant SaaS environment. Collaborate with data scientists, data engineers, and IT teams to define requirements and best practices for ML model development, deployment, and monitoring. Evaluate and recommend tools, platforms, and cloud technologies for ML Ops, ensuring alignment with enterprise architecture standards. Oversee the integration of ML pipelines with existing enterprise data and application architectures. Famil

Job Title: MLOps architect with Databricks implementation experience Location: Woodland Hills, CA (onsite) Duration: 12+ months contract Description: Architect and implement scalable AWS ML/AI cloud infrastructure in a multi-tenant SaaS environment.Collaborate with data scientists, data engineers, and IT teams to define requirements and best practices for ML model development, deployment, and monitoring.Evaluate and recommend tools, platforms, and cloud technologies for ML Ops, ensuring alignm

Position: ML Ops Engineer Location: Austin, TX and Sunnyvale, CA (Day 1 Onsite) - Need Locals Only Job Type: Contract Experience Required: 6 Plus years of experience in MLOps with strong knowledge in Kubernetes, Python, MongoDB and AWS. Technical skills: Python, Kubernetes, Mongo DB, Microservices, AWS SOLR ML operations, CI CD pipelines, LLM Good understanding of Apache SOLR Proficient with Linux administration. Knowledge of ML models and LLM. Ability to understand tools used by data scientist

Overview LMI is seeking an ML Ops Engineer to support the operationalization, sustainment, and continuous improvement of computer vision models used on autonomous edge platforms for a Special Operations customer. This role is responsible for the lifecycle management of machine learning models that operate onboard disconnected edge systems in tactical environments. A successful ML Ops Engineer ensures models remain accurate, testable, versioned, and safely deployable without requiring operators