

MLOps Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Engineer on a contract basis, focusing on deploying and monitoring ML models. Requires 3+ years in DevOps, strong Terraform and Kubernetes skills, Python proficiency, and ML deployment experience. Pay rate and contract length unspecified.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
744
-
ποΈ - Date discovered
September 19, 2025
π - Project duration
Unknown
-
ποΈ - Location type
Unknown
-
π - Contract type
Unknown
-
π - Security clearance
Unknown
-
π - Location detailed
Cupertino, CA
-
π§ - Skills detailed
#Docker #A/B Testing #Automation #Python #Observability #Scala #GCP (Google Cloud Platform) #FastAPI #Cloud #Data Science #Model Deployment #Infrastructure as Code (IaC) #Terraform #Deployment #Monitoring #Logging #Istio #Kubernetes #Programming #DevOps #ML (Machine Learning)
Role description
MLOps Engineer
ABOUT THIS FEATURED OPPORTUNITY
The MLOps Engineer will join the Channel Sales and Operations team and build and maintain infrastructure for deploying, monitoring, and scaling ML models, while enabling fast experimentation through CI/CD pipelines and efficient tooling. This role sits at the intersection of DevOps, ML engineering, and backend development, with a focus on automation, reliability, and performance.
THE OPPORTUNITY FOR YOU
β’ Design, automate, and maintain infrastructure-as-code with Terraform across cloud environments (GCP preferred).
β’ Manage containerized workloads with Kubernetes, Helm charts, and service meshes (Istio for advanced networking).
β’ Build and maintain scalable CI/CD pipelines for ML model training, validation, deployment, and monitoring.
β’ Develop and optimize FastAPI services for inference APIs and internal tooling.
β’ Implement deployment strategies (blue/green, canary, A/B testing) for ML models in production.
β’ Collaborate with data scientists to take models from experimentation to reliable production deployment.
β’ Utilize PromptQL and other observability tools to track model performance, monitor dashboards, and ensure reliability.
β’ Ensure infrastructure scaling, GPU/TPU utilization, and cost optimization in ML workloads.
β’ Troubleshoot and optimize distributed systems for high availability and performance.
KEY SUCCESS FACTORS
β’ 3+ years of DevOps and cloud infrastructure experience
β’ Strong experience with Terraform (commands like init, plan, apply, destroy) for IaC
β’ Hands-on with Kubernetes (kubectl get pods, kubectl scale deployment, kubectl describe, etc.) for scaling and monitoring workloads
β’ Experience creating and deploying Helm charts from Docker images
β’ Proficiency in Python with ability to write clean, testable, and scalable code
β’ Strong understanding of FastAPI and asynchronous programming (I/O bound vs CPU bound workloads)
β’ Machine learning and model deployment experience
β’ Understanding of the ML lifecycle : training β validation β deployment β monitoring
β’ Knowledge of monitoring, logging, and alerting for ML systems
NICE TO HAVES
β’ Familiarity with PromptQL for reviewing and analyzing ML dashboards
Our benefits package includes:
β’ Comprehensive medical benefits
β’ Competitive pay
β’ 401(k) retirement plan
β’ ...and much more!
About INSPYR Solutions
Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.
INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, INSPYR Solutions complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities.
MLOps Engineer
ABOUT THIS FEATURED OPPORTUNITY
The MLOps Engineer will join the Channel Sales and Operations team and build and maintain infrastructure for deploying, monitoring, and scaling ML models, while enabling fast experimentation through CI/CD pipelines and efficient tooling. This role sits at the intersection of DevOps, ML engineering, and backend development, with a focus on automation, reliability, and performance.
THE OPPORTUNITY FOR YOU
β’ Design, automate, and maintain infrastructure-as-code with Terraform across cloud environments (GCP preferred).
β’ Manage containerized workloads with Kubernetes, Helm charts, and service meshes (Istio for advanced networking).
β’ Build and maintain scalable CI/CD pipelines for ML model training, validation, deployment, and monitoring.
β’ Develop and optimize FastAPI services for inference APIs and internal tooling.
β’ Implement deployment strategies (blue/green, canary, A/B testing) for ML models in production.
β’ Collaborate with data scientists to take models from experimentation to reliable production deployment.
β’ Utilize PromptQL and other observability tools to track model performance, monitor dashboards, and ensure reliability.
β’ Ensure infrastructure scaling, GPU/TPU utilization, and cost optimization in ML workloads.
β’ Troubleshoot and optimize distributed systems for high availability and performance.
KEY SUCCESS FACTORS
β’ 3+ years of DevOps and cloud infrastructure experience
β’ Strong experience with Terraform (commands like init, plan, apply, destroy) for IaC
β’ Hands-on with Kubernetes (kubectl get pods, kubectl scale deployment, kubectl describe, etc.) for scaling and monitoring workloads
β’ Experience creating and deploying Helm charts from Docker images
β’ Proficiency in Python with ability to write clean, testable, and scalable code
β’ Strong understanding of FastAPI and asynchronous programming (I/O bound vs CPU bound workloads)
β’ Machine learning and model deployment experience
β’ Understanding of the ML lifecycle : training β validation β deployment β monitoring
β’ Knowledge of monitoring, logging, and alerting for ML systems
NICE TO HAVES
β’ Familiarity with PromptQL for reviewing and analyzing ML dashboards
Our benefits package includes:
β’ Comprehensive medical benefits
β’ Competitive pay
β’ 401(k) retirement plan
β’ ...and much more!
About INSPYR Solutions
Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.
INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, INSPYR Solutions complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities.